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You searched for subject:(Data uncertainty). Showing records 1 – 30 of 234 total matches.

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Colorado School of Mines

1. Pawelec, Iga. Uncertainty quantification in seismic imaging.

Degree: MS(M.S.), Geophysics, 2018, Colorado School of Mines

 To make informed decisions, one has to consider all available knowledge about the assessed problem. An important part of the decision-making process is understanding uncertainties… (more)

Subjects/Keywords: Seismic imaging; Data uncertainty; Uncertainty quantification

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APA (6th Edition):

Pawelec, I. (2018). Uncertainty quantification in seismic imaging. (Masters Thesis). Colorado School of Mines. Retrieved from http://hdl.handle.net/11124/172615

Chicago Manual of Style (16th Edition):

Pawelec, Iga. “Uncertainty quantification in seismic imaging.” 2018. Masters Thesis, Colorado School of Mines. Accessed September 27, 2020. http://hdl.handle.net/11124/172615.

MLA Handbook (7th Edition):

Pawelec, Iga. “Uncertainty quantification in seismic imaging.” 2018. Web. 27 Sep 2020.

Vancouver:

Pawelec I. Uncertainty quantification in seismic imaging. [Internet] [Masters thesis]. Colorado School of Mines; 2018. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/11124/172615.

Council of Science Editors:

Pawelec I. Uncertainty quantification in seismic imaging. [Masters Thesis]. Colorado School of Mines; 2018. Available from: http://hdl.handle.net/11124/172615


University of Arizona

2. Washburn, Ammon. High-Confidence Learning from Uncertain Data with High Dimensionality .

Degree: 2018, University of Arizona

 Some of the most challenging issues in big data are size, scalability and reliability. Big data, such as pictures, videos, and text, have innate structure… (more)

Subjects/Keywords: data classification; data uncertainty; high dimensional data; machine learning; optimization

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APA (6th Edition):

Washburn, A. (2018). High-Confidence Learning from Uncertain Data with High Dimensionality . (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/631476

Chicago Manual of Style (16th Edition):

Washburn, Ammon. “High-Confidence Learning from Uncertain Data with High Dimensionality .” 2018. Doctoral Dissertation, University of Arizona. Accessed September 27, 2020. http://hdl.handle.net/10150/631476.

MLA Handbook (7th Edition):

Washburn, Ammon. “High-Confidence Learning from Uncertain Data with High Dimensionality .” 2018. Web. 27 Sep 2020.

Vancouver:

Washburn A. High-Confidence Learning from Uncertain Data with High Dimensionality . [Internet] [Doctoral dissertation]. University of Arizona; 2018. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/10150/631476.

Council of Science Editors:

Washburn A. High-Confidence Learning from Uncertain Data with High Dimensionality . [Doctoral Dissertation]. University of Arizona; 2018. Available from: http://hdl.handle.net/10150/631476


University of California – Berkeley

3. Jeong, Seongeun. Understanding Snow Process Uncertainties and Their Impacts.

Degree: Civil and Environmental Engineering, 2009, University of California – Berkeley

 Prediction of snow in regional and global hydrological models has been a difficult task due to errors in the forcing data, subgrid-scale variability in the… (more)

Subjects/Keywords: Engineering, Civil; data assimilation; modeling; snow; uncertainty

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APA (6th Edition):

Jeong, S. (2009). Understanding Snow Process Uncertainties and Their Impacts. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/4zv592q2

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Jeong, Seongeun. “Understanding Snow Process Uncertainties and Their Impacts.” 2009. Thesis, University of California – Berkeley. Accessed September 27, 2020. http://www.escholarship.org/uc/item/4zv592q2.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Jeong, Seongeun. “Understanding Snow Process Uncertainties and Their Impacts.” 2009. Web. 27 Sep 2020.

Vancouver:

Jeong S. Understanding Snow Process Uncertainties and Their Impacts. [Internet] [Thesis]. University of California – Berkeley; 2009. [cited 2020 Sep 27]. Available from: http://www.escholarship.org/uc/item/4zv592q2.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Jeong S. Understanding Snow Process Uncertainties and Their Impacts. [Thesis]. University of California – Berkeley; 2009. Available from: http://www.escholarship.org/uc/item/4zv592q2

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Utah

4. Tang, Mingwang. New problems in exploring distributed data.

Degree: PhD, Computing (School of), 2015, University of Utah

 In the era of big data, many applications generate continuous online data from distributed locations, scattering devices, etc. Examples include data from social media, financial… (more)

Subjects/Keywords: data synopsis; distributed; histogram; monitoring; tracking; uncertainty

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APA (6th Edition):

Tang, M. (2015). New problems in exploring distributed data. (Doctoral Dissertation). University of Utah. Retrieved from http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/3829/rec/1689

Chicago Manual of Style (16th Edition):

Tang, Mingwang. “New problems in exploring distributed data.” 2015. Doctoral Dissertation, University of Utah. Accessed September 27, 2020. http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/3829/rec/1689.

MLA Handbook (7th Edition):

Tang, Mingwang. “New problems in exploring distributed data.” 2015. Web. 27 Sep 2020.

Vancouver:

Tang M. New problems in exploring distributed data. [Internet] [Doctoral dissertation]. University of Utah; 2015. [cited 2020 Sep 27]. Available from: http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/3829/rec/1689.

Council of Science Editors:

Tang M. New problems in exploring distributed data. [Doctoral Dissertation]. University of Utah; 2015. Available from: http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/3829/rec/1689

5. Shi, Yingxi. Critical Evaluations Of Modis And Misr Satellite Aerosol Products For Aerosol Modeling Applications.

Degree: PhD, Atmospheric Sciences, 2015, University of North Dakota

  The study of uncertainties in satellite aerosol products is essential to aerosol data assimilation and modeling efforts. In this study, with the assistance of… (more)

Subjects/Keywords: Aerosols; Data assimilation; Satellite retrievals; Uncertainty evaluations

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APA (6th Edition):

Shi, Y. (2015). Critical Evaluations Of Modis And Misr Satellite Aerosol Products For Aerosol Modeling Applications. (Doctoral Dissertation). University of North Dakota. Retrieved from https://commons.und.edu/theses/1963

Chicago Manual of Style (16th Edition):

Shi, Yingxi. “Critical Evaluations Of Modis And Misr Satellite Aerosol Products For Aerosol Modeling Applications.” 2015. Doctoral Dissertation, University of North Dakota. Accessed September 27, 2020. https://commons.und.edu/theses/1963.

MLA Handbook (7th Edition):

Shi, Yingxi. “Critical Evaluations Of Modis And Misr Satellite Aerosol Products For Aerosol Modeling Applications.” 2015. Web. 27 Sep 2020.

Vancouver:

Shi Y. Critical Evaluations Of Modis And Misr Satellite Aerosol Products For Aerosol Modeling Applications. [Internet] [Doctoral dissertation]. University of North Dakota; 2015. [cited 2020 Sep 27]. Available from: https://commons.und.edu/theses/1963.

Council of Science Editors:

Shi Y. Critical Evaluations Of Modis And Misr Satellite Aerosol Products For Aerosol Modeling Applications. [Doctoral Dissertation]. University of North Dakota; 2015. Available from: https://commons.und.edu/theses/1963


University of New South Wales

6. Pathiraja, Sahani. Improving Data Assimilation Algorithms for Enhanced Environmental Predictions.

Degree: Civil & Environmental Engineering, 2018, University of New South Wales

Data Assimilation (DA) methods provide a means of combining model output with observations based on their respective uncertainties. They are considered an invaluable tool in… (more)

Subjects/Keywords: Uncertainty quantification; Data assimilation; Forecasting; Hydrology; Meteorology

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APA (6th Edition):

Pathiraja, S. (2018). Improving Data Assimilation Algorithms for Enhanced Environmental Predictions. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/59579 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:49002/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Pathiraja, Sahani. “Improving Data Assimilation Algorithms for Enhanced Environmental Predictions.” 2018. Doctoral Dissertation, University of New South Wales. Accessed September 27, 2020. http://handle.unsw.edu.au/1959.4/59579 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:49002/SOURCE02?view=true.

MLA Handbook (7th Edition):

Pathiraja, Sahani. “Improving Data Assimilation Algorithms for Enhanced Environmental Predictions.” 2018. Web. 27 Sep 2020.

Vancouver:

Pathiraja S. Improving Data Assimilation Algorithms for Enhanced Environmental Predictions. [Internet] [Doctoral dissertation]. University of New South Wales; 2018. [cited 2020 Sep 27]. Available from: http://handle.unsw.edu.au/1959.4/59579 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:49002/SOURCE02?view=true.

Council of Science Editors:

Pathiraja S. Improving Data Assimilation Algorithms for Enhanced Environmental Predictions. [Doctoral Dissertation]. University of New South Wales; 2018. Available from: http://handle.unsw.edu.au/1959.4/59579 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:49002/SOURCE02?view=true


University of Sydney

7. Nguyen, Phuc Vuong. Modelling uncertainty in population monitoring data .

Degree: 2016, University of Sydney

 Uncertainties in ecology are pervasive, and therefore, communicating the level of uncertainty for any inference derived from scientific research is key to sound decision-making and… (more)

Subjects/Keywords: uncertainty; modelling; population; monitoring; data; demography

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APA (6th Edition):

Nguyen, P. V. (2016). Modelling uncertainty in population monitoring data . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/14532

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Nguyen, Phuc Vuong. “Modelling uncertainty in population monitoring data .” 2016. Thesis, University of Sydney. Accessed September 27, 2020. http://hdl.handle.net/2123/14532.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Nguyen, Phuc Vuong. “Modelling uncertainty in population monitoring data .” 2016. Web. 27 Sep 2020.

Vancouver:

Nguyen PV. Modelling uncertainty in population monitoring data . [Internet] [Thesis]. University of Sydney; 2016. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/2123/14532.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Nguyen PV. Modelling uncertainty in population monitoring data . [Thesis]. University of Sydney; 2016. Available from: http://hdl.handle.net/2123/14532

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Delft University of Technology

8. Arkesteijn, E.C.M.M. (author). Uncertainty assessment of the geometry of an aquitard using an EnKF and EnKF-GMM.

Degree: 2014, Delft University of Technology

Hydraulic head data is frequently used for the calibration of groundwater flow models, usually with the main objective to improve the model performance. The hydraulic… (more)

Subjects/Keywords: data assimilation; EnKF; EnKF-GMM; uncertainty assessment

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APA (6th Edition):

Arkesteijn, E. C. M. M. (. (2014). Uncertainty assessment of the geometry of an aquitard using an EnKF and EnKF-GMM. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:1672b38e-fcf6-4f9f-9299-e23e241f710f

Chicago Manual of Style (16th Edition):

Arkesteijn, E C M M (author). “Uncertainty assessment of the geometry of an aquitard using an EnKF and EnKF-GMM.” 2014. Masters Thesis, Delft University of Technology. Accessed September 27, 2020. http://resolver.tudelft.nl/uuid:1672b38e-fcf6-4f9f-9299-e23e241f710f.

MLA Handbook (7th Edition):

Arkesteijn, E C M M (author). “Uncertainty assessment of the geometry of an aquitard using an EnKF and EnKF-GMM.” 2014. Web. 27 Sep 2020.

Vancouver:

Arkesteijn ECMM(. Uncertainty assessment of the geometry of an aquitard using an EnKF and EnKF-GMM. [Internet] [Masters thesis]. Delft University of Technology; 2014. [cited 2020 Sep 27]. Available from: http://resolver.tudelft.nl/uuid:1672b38e-fcf6-4f9f-9299-e23e241f710f.

Council of Science Editors:

Arkesteijn ECMM(. Uncertainty assessment of the geometry of an aquitard using an EnKF and EnKF-GMM. [Masters Thesis]. Delft University of Technology; 2014. Available from: http://resolver.tudelft.nl/uuid:1672b38e-fcf6-4f9f-9299-e23e241f710f


Virginia Tech

9. McDonald, Walter Miller. Stormwater Monitoring: Evaluation of Uncertainty due to Inadequate Temporal Sampling and Applications for Engineering Education.

Degree: PhD, Civil Engineering, 2016, Virginia Tech

 The world is faced with uncertain and dramatic changes in water movement, availability, and quality are due to human-induced stressors such as population growth, climatic… (more)

Subjects/Keywords: stormwater; data uncertainty; regional regression; engineering education

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APA (6th Edition):

McDonald, W. M. (2016). Stormwater Monitoring: Evaluation of Uncertainty due to Inadequate Temporal Sampling and Applications for Engineering Education. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/71696

Chicago Manual of Style (16th Edition):

McDonald, Walter Miller. “Stormwater Monitoring: Evaluation of Uncertainty due to Inadequate Temporal Sampling and Applications for Engineering Education.” 2016. Doctoral Dissertation, Virginia Tech. Accessed September 27, 2020. http://hdl.handle.net/10919/71696.

MLA Handbook (7th Edition):

McDonald, Walter Miller. “Stormwater Monitoring: Evaluation of Uncertainty due to Inadequate Temporal Sampling and Applications for Engineering Education.” 2016. Web. 27 Sep 2020.

Vancouver:

McDonald WM. Stormwater Monitoring: Evaluation of Uncertainty due to Inadequate Temporal Sampling and Applications for Engineering Education. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/10919/71696.

Council of Science Editors:

McDonald WM. Stormwater Monitoring: Evaluation of Uncertainty due to Inadequate Temporal Sampling and Applications for Engineering Education. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/71696


University of Alberta

10. Wilde, Brandon Jesse. Data spacing and uncertainty.

Degree: MS, Department of Civil and Environmental Engineering, 2010, University of Alberta

 Modeling spatial variables involves uncertainty. Uncertainty is affected by the degree to which a spatial variable has been sampled: decreased spacing between samples leads to… (more)

Subjects/Keywords: data spacing; sampling; uncertainty; data density; sequential Gaussian simulation

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APA (6th Edition):

Wilde, B. J. (2010). Data spacing and uncertainty. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/s4655g713

Chicago Manual of Style (16th Edition):

Wilde, Brandon Jesse. “Data spacing and uncertainty.” 2010. Masters Thesis, University of Alberta. Accessed September 27, 2020. https://era.library.ualberta.ca/files/s4655g713.

MLA Handbook (7th Edition):

Wilde, Brandon Jesse. “Data spacing and uncertainty.” 2010. Web. 27 Sep 2020.

Vancouver:

Wilde BJ. Data spacing and uncertainty. [Internet] [Masters thesis]. University of Alberta; 2010. [cited 2020 Sep 27]. Available from: https://era.library.ualberta.ca/files/s4655g713.

Council of Science Editors:

Wilde BJ. Data spacing and uncertainty. [Masters Thesis]. University of Alberta; 2010. Available from: https://era.library.ualberta.ca/files/s4655g713


Vanderbilt University

11. Sankararaman, Shankar. Uncertainty Quantification and Integration in Engineering Systems.

Degree: PhD, Civil Engineering, 2012, Vanderbilt University

 A comprehensive framework for the treatment of uncertainty is essential to facilitate decision-making in engineering systems at every stage of the life cycle, such as… (more)

Subjects/Keywords: model uncertainty; data uncertainty; verification and validation; model calibration; Bayesian networks; inverse problems; sensitivity analysis

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APA (6th Edition):

Sankararaman, S. (2012). Uncertainty Quantification and Integration in Engineering Systems. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/10567

Chicago Manual of Style (16th Edition):

Sankararaman, Shankar. “Uncertainty Quantification and Integration in Engineering Systems.” 2012. Doctoral Dissertation, Vanderbilt University. Accessed September 27, 2020. http://hdl.handle.net/1803/10567.

MLA Handbook (7th Edition):

Sankararaman, Shankar. “Uncertainty Quantification and Integration in Engineering Systems.” 2012. Web. 27 Sep 2020.

Vancouver:

Sankararaman S. Uncertainty Quantification and Integration in Engineering Systems. [Internet] [Doctoral dissertation]. Vanderbilt University; 2012. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1803/10567.

Council of Science Editors:

Sankararaman S. Uncertainty Quantification and Integration in Engineering Systems. [Doctoral Dissertation]. Vanderbilt University; 2012. Available from: http://hdl.handle.net/1803/10567

12. Wu, Jinlong. Predictive Turbulence Modeling with Bayesian Inference and Physics-Informed Machine Learning.

Degree: PhD, Aerospace Engineering, 2018, Virginia Tech

 Reynolds-Averaged Navier–Stokes (RANS) simulations are widely used for engineering design and analysis involving turbulent flows. In RANS simulations, the Reynolds stress needs closure models and… (more)

Subjects/Keywords: Turbulence modeling; RANS; Model-form uncertainty; Data-driven; Uncertainty quantification; Bayesian Inference; Machine learning

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APA (6th Edition):

Wu, J. (2018). Predictive Turbulence Modeling with Bayesian Inference and Physics-Informed Machine Learning. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/85129

Chicago Manual of Style (16th Edition):

Wu, Jinlong. “Predictive Turbulence Modeling with Bayesian Inference and Physics-Informed Machine Learning.” 2018. Doctoral Dissertation, Virginia Tech. Accessed September 27, 2020. http://hdl.handle.net/10919/85129.

MLA Handbook (7th Edition):

Wu, Jinlong. “Predictive Turbulence Modeling with Bayesian Inference and Physics-Informed Machine Learning.” 2018. Web. 27 Sep 2020.

Vancouver:

Wu J. Predictive Turbulence Modeling with Bayesian Inference and Physics-Informed Machine Learning. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/10919/85129.

Council of Science Editors:

Wu J. Predictive Turbulence Modeling with Bayesian Inference and Physics-Informed Machine Learning. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/85129

13. Ahmed, Alaa Hassan. Fusing uncertain data with probabilities.

Degree: 2016, NC Docks

 Discovering the correct data among the uncertain and possibly conflicting mined data is the main goal of data fusion. The recent research in fusing uncertain… (more)

Subjects/Keywords: Data integration (Computer science); Uncertainty (Information theory); Probabilities $x Data processing; Data mining

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APA (6th Edition):

Ahmed, A. H. (2016). Fusing uncertain data with probabilities. (Thesis). NC Docks. Retrieved from http://libres.uncg.edu/ir/uncg/f/Ahmed_uncg_0154M_11970.pdf

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ahmed, Alaa Hassan. “Fusing uncertain data with probabilities.” 2016. Thesis, NC Docks. Accessed September 27, 2020. http://libres.uncg.edu/ir/uncg/f/Ahmed_uncg_0154M_11970.pdf.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ahmed, Alaa Hassan. “Fusing uncertain data with probabilities.” 2016. Web. 27 Sep 2020.

Vancouver:

Ahmed AH. Fusing uncertain data with probabilities. [Internet] [Thesis]. NC Docks; 2016. [cited 2020 Sep 27]. Available from: http://libres.uncg.edu/ir/uncg/f/Ahmed_uncg_0154M_11970.pdf.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ahmed AH. Fusing uncertain data with probabilities. [Thesis]. NC Docks; 2016. Available from: http://libres.uncg.edu/ir/uncg/f/Ahmed_uncg_0154M_11970.pdf

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

14. Liu, Hongli. Improved Data Uncertainty Handling in Hydrologic Modeling and Forecasting Applications.

Degree: 2019, University of Waterloo

 In hydrologic modeling and forecasting applications, many steps are needed. The steps that are relevant to this thesis include watershed discretization, model calibration, and data(more)

Subjects/Keywords: Hydrologic modeling; Model calibration; Data assimilation; Streamflow ensemble forecasting; Spatial discretization; Ensemble climate; Ensemble flow; Ensemble Kalman filter; Parameter uncertainty; Data uncertainty; Prediction uncertainty

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APA (6th Edition):

Liu, H. (2019). Improved Data Uncertainty Handling in Hydrologic Modeling and Forecasting Applications. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/14498

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Liu, Hongli. “Improved Data Uncertainty Handling in Hydrologic Modeling and Forecasting Applications.” 2019. Thesis, University of Waterloo. Accessed September 27, 2020. http://hdl.handle.net/10012/14498.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Liu, Hongli. “Improved Data Uncertainty Handling in Hydrologic Modeling and Forecasting Applications.” 2019. Web. 27 Sep 2020.

Vancouver:

Liu H. Improved Data Uncertainty Handling in Hydrologic Modeling and Forecasting Applications. [Internet] [Thesis]. University of Waterloo; 2019. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/10012/14498.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Liu H. Improved Data Uncertainty Handling in Hydrologic Modeling and Forecasting Applications. [Thesis]. University of Waterloo; 2019. Available from: http://hdl.handle.net/10012/14498

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Hong Kong University of Science and Technology

15. Zhao, Zhou. Uncertain data processing and applications.

Degree: 2015, Hong Kong University of Science and Technology

Data uncertainty is inherent in many important real-world applications. In this thesis, we focus on the problem of missing value estimation in uncertain data processing.… (more)

Subjects/Keywords: Radio frequency identification systems ; Data processing ; Electronic data processing ; Distributed processing ; Uncertainty (Information theory)

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APA (6th Edition):

Zhao, Z. (2015). Uncertain data processing and applications. (Thesis). Hong Kong University of Science and Technology. Retrieved from http://repository.ust.hk/ir/Record/1783.1-74335 ; https://doi.org/10.14711/thesis-b1450545 ; http://repository.ust.hk/ir/bitstream/1783.1-74335/1/th_redirect.html

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Zhao, Zhou. “Uncertain data processing and applications.” 2015. Thesis, Hong Kong University of Science and Technology. Accessed September 27, 2020. http://repository.ust.hk/ir/Record/1783.1-74335 ; https://doi.org/10.14711/thesis-b1450545 ; http://repository.ust.hk/ir/bitstream/1783.1-74335/1/th_redirect.html.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Zhao, Zhou. “Uncertain data processing and applications.” 2015. Web. 27 Sep 2020.

Vancouver:

Zhao Z. Uncertain data processing and applications. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2015. [cited 2020 Sep 27]. Available from: http://repository.ust.hk/ir/Record/1783.1-74335 ; https://doi.org/10.14711/thesis-b1450545 ; http://repository.ust.hk/ir/bitstream/1783.1-74335/1/th_redirect.html.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Zhao Z. Uncertain data processing and applications. [Thesis]. Hong Kong University of Science and Technology; 2015. Available from: http://repository.ust.hk/ir/Record/1783.1-74335 ; https://doi.org/10.14711/thesis-b1450545 ; http://repository.ust.hk/ir/bitstream/1783.1-74335/1/th_redirect.html

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Oulu

16. Alasalmi, T. (Tuomo). Uncertainty of classification on limited data.

Degree: 2020, University of Oulu

Abstract It is common knowledge that even simple machine learning algorithms can improve in performance with large, good quality data sets. However, limited data sets,… (more)

Subjects/Keywords: classification; missing data; probability; small data; uncertainty; epävarmuus; luokittelu; pieni aineisto; puuttuva aineisto; todennäköisyys

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Alasalmi, T. (. (2020). Uncertainty of classification on limited data. (Doctoral Dissertation). University of Oulu. Retrieved from http://urn.fi/urn:isbn:9789526227115

Chicago Manual of Style (16th Edition):

Alasalmi, T (Tuomo). “Uncertainty of classification on limited data.” 2020. Doctoral Dissertation, University of Oulu. Accessed September 27, 2020. http://urn.fi/urn:isbn:9789526227115.

MLA Handbook (7th Edition):

Alasalmi, T (Tuomo). “Uncertainty of classification on limited data.” 2020. Web. 27 Sep 2020.

Vancouver:

Alasalmi T(. Uncertainty of classification on limited data. [Internet] [Doctoral dissertation]. University of Oulu; 2020. [cited 2020 Sep 27]. Available from: http://urn.fi/urn:isbn:9789526227115.

Council of Science Editors:

Alasalmi T(. Uncertainty of classification on limited data. [Doctoral Dissertation]. University of Oulu; 2020. Available from: http://urn.fi/urn:isbn:9789526227115


University of Hong Kong

17. 王亮. Frequent itemsets mining on uncertain databases.

Degree: 2010, University of Hong Kong

Subjects/Keywords: Data mining.; Uncertainty (Information theory)

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

王亮. (2010). Frequent itemsets mining on uncertain databases. (Thesis). University of Hong Kong. Retrieved from http://hdl.handle.net/10722/134093

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

王亮. “Frequent itemsets mining on uncertain databases.” 2010. Thesis, University of Hong Kong. Accessed September 27, 2020. http://hdl.handle.net/10722/134093.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

王亮. “Frequent itemsets mining on uncertain databases.” 2010. Web. 27 Sep 2020.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

王亮. Frequent itemsets mining on uncertain databases. [Internet] [Thesis]. University of Hong Kong; 2010. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/10722/134093.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

王亮. Frequent itemsets mining on uncertain databases. [Thesis]. University of Hong Kong; 2010. Available from: http://hdl.handle.net/10722/134093

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation


Texas A&M University

18. Herrera, Michael Aaron. Techniques for the Improvement of Numerical Weather Prediction: Investigating the Dynamics of Forecast Uncertainty and the Implementation of Regionally Enhanced Global Data Assimilation.

Degree: PhD, Atmospheric Sciences, 2016, Texas A&M University

 This dissertation describes and shows results from two projects which focused on investigating and improving current methods of numerical weather prediction. First, we show a… (more)

Subjects/Keywords: data assimilation; numerical weather prediction; ensemble forecasting; forecast uncertainty

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Herrera, M. A. (2016). Techniques for the Improvement of Numerical Weather Prediction: Investigating the Dynamics of Forecast Uncertainty and the Implementation of Regionally Enhanced Global Data Assimilation. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/159097

Chicago Manual of Style (16th Edition):

Herrera, Michael Aaron. “Techniques for the Improvement of Numerical Weather Prediction: Investigating the Dynamics of Forecast Uncertainty and the Implementation of Regionally Enhanced Global Data Assimilation.” 2016. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/159097.

MLA Handbook (7th Edition):

Herrera, Michael Aaron. “Techniques for the Improvement of Numerical Weather Prediction: Investigating the Dynamics of Forecast Uncertainty and the Implementation of Regionally Enhanced Global Data Assimilation.” 2016. Web. 27 Sep 2020.

Vancouver:

Herrera MA. Techniques for the Improvement of Numerical Weather Prediction: Investigating the Dynamics of Forecast Uncertainty and the Implementation of Regionally Enhanced Global Data Assimilation. [Internet] [Doctoral dissertation]. Texas A&M University; 2016. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/159097.

Council of Science Editors:

Herrera MA. Techniques for the Improvement of Numerical Weather Prediction: Investigating the Dynamics of Forecast Uncertainty and the Implementation of Regionally Enhanced Global Data Assimilation. [Doctoral Dissertation]. Texas A&M University; 2016. Available from: http://hdl.handle.net/1969.1/159097


McMaster University

19. Richard, Michael R. Determining the Size of a Galaxy's Globular Cluster Population through Imputation of Incomplete Data with Measurement Uncertainty.

Degree: MSc, 2015, McMaster University

A globular cluster is a collection of stars that orbits the center of its galaxy as a single satellite. Understanding what influences the formations of… (more)

Subjects/Keywords: Missing Data; Imputation; Predictive Mean Matching; Measurement Uncertainty; Globular Clusters

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Richard, M. R. (2015). Determining the Size of a Galaxy's Globular Cluster Population through Imputation of Incomplete Data with Measurement Uncertainty. (Masters Thesis). McMaster University. Retrieved from http://hdl.handle.net/11375/18252

Chicago Manual of Style (16th Edition):

Richard, Michael R. “Determining the Size of a Galaxy's Globular Cluster Population through Imputation of Incomplete Data with Measurement Uncertainty.” 2015. Masters Thesis, McMaster University. Accessed September 27, 2020. http://hdl.handle.net/11375/18252.

MLA Handbook (7th Edition):

Richard, Michael R. “Determining the Size of a Galaxy's Globular Cluster Population through Imputation of Incomplete Data with Measurement Uncertainty.” 2015. Web. 27 Sep 2020.

Vancouver:

Richard MR. Determining the Size of a Galaxy's Globular Cluster Population through Imputation of Incomplete Data with Measurement Uncertainty. [Internet] [Masters thesis]. McMaster University; 2015. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/11375/18252.

Council of Science Editors:

Richard MR. Determining the Size of a Galaxy's Globular Cluster Population through Imputation of Incomplete Data with Measurement Uncertainty. [Masters Thesis]. McMaster University; 2015. Available from: http://hdl.handle.net/11375/18252


Western Michigan University

20. Sung, Pei-Ju. The Impact of Uncertainty on Data Revision.

Degree: PhD, Economics, 2015, Western Michigan University

  Initial estimates of macroeconomic variables based on incomplete source data can be unreliable. Because of the methodology used by reporting agencies and the presence… (more)

Subjects/Keywords: Data revision; rationality; forecasting; real-time analysis; monetary; uncertainty; Economics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Sung, P. (2015). The Impact of Uncertainty on Data Revision. (Doctoral Dissertation). Western Michigan University. Retrieved from https://scholarworks.wmich.edu/dissertations/1198

Chicago Manual of Style (16th Edition):

Sung, Pei-Ju. “The Impact of Uncertainty on Data Revision.” 2015. Doctoral Dissertation, Western Michigan University. Accessed September 27, 2020. https://scholarworks.wmich.edu/dissertations/1198.

MLA Handbook (7th Edition):

Sung, Pei-Ju. “The Impact of Uncertainty on Data Revision.” 2015. Web. 27 Sep 2020.

Vancouver:

Sung P. The Impact of Uncertainty on Data Revision. [Internet] [Doctoral dissertation]. Western Michigan University; 2015. [cited 2020 Sep 27]. Available from: https://scholarworks.wmich.edu/dissertations/1198.

Council of Science Editors:

Sung P. The Impact of Uncertainty on Data Revision. [Doctoral Dissertation]. Western Michigan University; 2015. Available from: https://scholarworks.wmich.edu/dissertations/1198


Colorado State University

21. González-Nicolás Álvarez, Ana. Methodologies to detect leakages from geological carbon storage sites.

Degree: PhD, Civil and Environmental Engineering, 2014, Colorado State University

 Geological carbon storage (GCS) has been proposed as a favorable technology to reduce carbon dioxide (CO2) emissions to the atmosphere. Candidate storage formations include abandoned… (more)

Subjects/Keywords: carbon sequestration; CO2 leakage; data assimilation; ECLIPSE; multiphase flow; uncertainty

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APA (6th Edition):

González-Nicolás Álvarez, A. (2014). Methodologies to detect leakages from geological carbon storage sites. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/83767

Chicago Manual of Style (16th Edition):

González-Nicolás Álvarez, Ana. “Methodologies to detect leakages from geological carbon storage sites.” 2014. Doctoral Dissertation, Colorado State University. Accessed September 27, 2020. http://hdl.handle.net/10217/83767.

MLA Handbook (7th Edition):

González-Nicolás Álvarez, Ana. “Methodologies to detect leakages from geological carbon storage sites.” 2014. Web. 27 Sep 2020.

Vancouver:

González-Nicolás Álvarez A. Methodologies to detect leakages from geological carbon storage sites. [Internet] [Doctoral dissertation]. Colorado State University; 2014. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/10217/83767.

Council of Science Editors:

González-Nicolás Álvarez A. Methodologies to detect leakages from geological carbon storage sites. [Doctoral Dissertation]. Colorado State University; 2014. Available from: http://hdl.handle.net/10217/83767


University of Manchester

22. Sanchez Serrano, Fernando Rene. A PROBABILISTIC APPROACH TO UNCERTAINTY QUANTIFICATION IN PAY-AS-YOU-GO DATA INTEGRATION.

Degree: 2019, University of Manchester

 The use of Web standards, compact publication guidelines, and open data initiatives have motivated many public and private organisations to publish data on the Web,… (more)

Subjects/Keywords: DATA INTEGRATION; PAY AS YOU GO; PROBABILISTIC APPROACH; UNCERTAINTY QUANTIFICATION

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Sanchez Serrano, F. R. (2019). A PROBABILISTIC APPROACH TO UNCERTAINTY QUANTIFICATION IN PAY-AS-YOU-GO DATA INTEGRATION. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:319123

Chicago Manual of Style (16th Edition):

Sanchez Serrano, Fernando Rene. “A PROBABILISTIC APPROACH TO UNCERTAINTY QUANTIFICATION IN PAY-AS-YOU-GO DATA INTEGRATION.” 2019. Doctoral Dissertation, University of Manchester. Accessed September 27, 2020. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:319123.

MLA Handbook (7th Edition):

Sanchez Serrano, Fernando Rene. “A PROBABILISTIC APPROACH TO UNCERTAINTY QUANTIFICATION IN PAY-AS-YOU-GO DATA INTEGRATION.” 2019. Web. 27 Sep 2020.

Vancouver:

Sanchez Serrano FR. A PROBABILISTIC APPROACH TO UNCERTAINTY QUANTIFICATION IN PAY-AS-YOU-GO DATA INTEGRATION. [Internet] [Doctoral dissertation]. University of Manchester; 2019. [cited 2020 Sep 27]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:319123.

Council of Science Editors:

Sanchez Serrano FR. A PROBABILISTIC APPROACH TO UNCERTAINTY QUANTIFICATION IN PAY-AS-YOU-GO DATA INTEGRATION. [Doctoral Dissertation]. University of Manchester; 2019. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:319123

23. Wang, Jianxun. Physics-Informed, Data-Driven Framework for Model-Form Uncertainty Estimation and Reduction in RANS Simulations.

Degree: PhD, Aerospace and Ocean Engineering, 2017, Virginia Tech

 Computational fluid dynamics (CFD) has been widely used to simulate turbulent flows. Although an increased availability of computational resources has enabled high-fidelity simulations (e.g. large… (more)

Subjects/Keywords: Uncertainty quantification; Data-driven; RANS; Turbulence modeling; Machine learning; Random matrix

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APA (6th Edition):

Wang, J. (2017). Physics-Informed, Data-Driven Framework for Model-Form Uncertainty Estimation and Reduction in RANS Simulations. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/77035

Chicago Manual of Style (16th Edition):

Wang, Jianxun. “Physics-Informed, Data-Driven Framework for Model-Form Uncertainty Estimation and Reduction in RANS Simulations.” 2017. Doctoral Dissertation, Virginia Tech. Accessed September 27, 2020. http://hdl.handle.net/10919/77035.

MLA Handbook (7th Edition):

Wang, Jianxun. “Physics-Informed, Data-Driven Framework for Model-Form Uncertainty Estimation and Reduction in RANS Simulations.” 2017. Web. 27 Sep 2020.

Vancouver:

Wang J. Physics-Informed, Data-Driven Framework for Model-Form Uncertainty Estimation and Reduction in RANS Simulations. [Internet] [Doctoral dissertation]. Virginia Tech; 2017. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/10919/77035.

Council of Science Editors:

Wang J. Physics-Informed, Data-Driven Framework for Model-Form Uncertainty Estimation and Reduction in RANS Simulations. [Doctoral Dissertation]. Virginia Tech; 2017. Available from: http://hdl.handle.net/10919/77035


Virginia Tech

24. Foy, Andrew Scott. Making Sense Out of Uncertainty in Geospatial Data.

Degree: PhD, Geospatial and Environmental Analysis, 2011, Virginia Tech

Uncertainty in geospatial data fusion is a major concern for scientists because society is increasing its use of geospatial technology and generalization is inherent to… (more)

Subjects/Keywords: GIS; uncertainty; spatial data fusion; error-band framework; GIS tool; overlays

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Foy, A. S. (2011). Making Sense Out of Uncertainty in Geospatial Data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/39175

Chicago Manual of Style (16th Edition):

Foy, Andrew Scott. “Making Sense Out of Uncertainty in Geospatial Data.” 2011. Doctoral Dissertation, Virginia Tech. Accessed September 27, 2020. http://hdl.handle.net/10919/39175.

MLA Handbook (7th Edition):

Foy, Andrew Scott. “Making Sense Out of Uncertainty in Geospatial Data.” 2011. Web. 27 Sep 2020.

Vancouver:

Foy AS. Making Sense Out of Uncertainty in Geospatial Data. [Internet] [Doctoral dissertation]. Virginia Tech; 2011. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/10919/39175.

Council of Science Editors:

Foy AS. Making Sense Out of Uncertainty in Geospatial Data. [Doctoral Dissertation]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/39175


Cranfield University

25. Schwabe, Oliver. A geometrical framework for forecasting cost uncertainty in innovative high value manufacturing.

Degree: 2018, Cranfield University

 Increasing competition and regulation are raising the pressure on manufacturing organisations to innovate their products. Innovation is fraught by significant uncertainty of whole product life… (more)

Subjects/Keywords: Cost estimation; Cost uncertainty forecasting; Geometric forecasting; Scarce data

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APA (6th Edition):

Schwabe, O. (2018). A geometrical framework for forecasting cost uncertainty in innovative high value manufacturing. (Thesis). Cranfield University. Retrieved from http://dspace.lib.cranfield.ac.uk/handle/1826/13616

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Schwabe, Oliver. “A geometrical framework for forecasting cost uncertainty in innovative high value manufacturing.” 2018. Thesis, Cranfield University. Accessed September 27, 2020. http://dspace.lib.cranfield.ac.uk/handle/1826/13616.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Schwabe, Oliver. “A geometrical framework for forecasting cost uncertainty in innovative high value manufacturing.” 2018. Web. 27 Sep 2020.

Vancouver:

Schwabe O. A geometrical framework for forecasting cost uncertainty in innovative high value manufacturing. [Internet] [Thesis]. Cranfield University; 2018. [cited 2020 Sep 27]. Available from: http://dspace.lib.cranfield.ac.uk/handle/1826/13616.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Schwabe O. A geometrical framework for forecasting cost uncertainty in innovative high value manufacturing. [Thesis]. Cranfield University; 2018. Available from: http://dspace.lib.cranfield.ac.uk/handle/1826/13616

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Illinois – Chicago

26. Ayala, Daniel. Spatio-temporal Matching for Urban Transportation Applications.

Degree: 2017, University of Illinois – Chicago

 In this work we present a search problem in which mobile agents are searching for static resources. Each agent wants to obtain exactly one resource.… (more)

Subjects/Keywords: Spatio-temporal Matching; Game Theory; Pricing Scheme; Data Uncertainty

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APA (6th Edition):

Ayala, D. (2017). Spatio-temporal Matching for Urban Transportation Applications. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/21744

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ayala, Daniel. “Spatio-temporal Matching for Urban Transportation Applications.” 2017. Thesis, University of Illinois – Chicago. Accessed September 27, 2020. http://hdl.handle.net/10027/21744.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ayala, Daniel. “Spatio-temporal Matching for Urban Transportation Applications.” 2017. Web. 27 Sep 2020.

Vancouver:

Ayala D. Spatio-temporal Matching for Urban Transportation Applications. [Internet] [Thesis]. University of Illinois – Chicago; 2017. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/10027/21744.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ayala D. Spatio-temporal Matching for Urban Transportation Applications. [Thesis]. University of Illinois – Chicago; 2017. Available from: http://hdl.handle.net/10027/21744

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Cranfield University

27. Schwabe, Oliver. A geometrical framework for forecasting cost uncertainty in innovative high value manufacturing.

Degree: PhD, 2018, Cranfield University

 Increasing competition and regulation are raising the pressure on manufacturing organisations to innovate their products. Innovation is fraught by significant uncertainty of whole product life… (more)

Subjects/Keywords: Cost estimation; Cost uncertainty forecasting; Geometric forecasting; Scarce data

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Schwabe, O. (2018). A geometrical framework for forecasting cost uncertainty in innovative high value manufacturing. (Doctoral Dissertation). Cranfield University. Retrieved from http://dspace.lib.cranfield.ac.uk/handle/1826/13616 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.761429

Chicago Manual of Style (16th Edition):

Schwabe, Oliver. “A geometrical framework for forecasting cost uncertainty in innovative high value manufacturing.” 2018. Doctoral Dissertation, Cranfield University. Accessed September 27, 2020. http://dspace.lib.cranfield.ac.uk/handle/1826/13616 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.761429.

MLA Handbook (7th Edition):

Schwabe, Oliver. “A geometrical framework for forecasting cost uncertainty in innovative high value manufacturing.” 2018. Web. 27 Sep 2020.

Vancouver:

Schwabe O. A geometrical framework for forecasting cost uncertainty in innovative high value manufacturing. [Internet] [Doctoral dissertation]. Cranfield University; 2018. [cited 2020 Sep 27]. Available from: http://dspace.lib.cranfield.ac.uk/handle/1826/13616 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.761429.

Council of Science Editors:

Schwabe O. A geometrical framework for forecasting cost uncertainty in innovative high value manufacturing. [Doctoral Dissertation]. Cranfield University; 2018. Available from: http://dspace.lib.cranfield.ac.uk/handle/1826/13616 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.761429

28. Radaideh, Majdi Ibrahim Ahmad. A novel framework for data-driven modeling, uncertainty quantification, and deep learning of nuclear reactor simulations.

Degree: PhD, Nuclear, Plasma, Radiolgc Engr, 2019, University of Illinois – Urbana-Champaign

 This work presents a novel and modern method for reactor modeling, simulation, and uncertainty characterization through an integrated framework developed under the terminology of combining… (more)

Subjects/Keywords: Nuclear Multiphysics; Uncertainty Quantification; Deep Learning; Data-driven Modeling; Bayesian Statistics

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APA (6th Edition):

Radaideh, M. I. A. (2019). A novel framework for data-driven modeling, uncertainty quantification, and deep learning of nuclear reactor simulations. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/106162

Chicago Manual of Style (16th Edition):

Radaideh, Majdi Ibrahim Ahmad. “A novel framework for data-driven modeling, uncertainty quantification, and deep learning of nuclear reactor simulations.” 2019. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed September 27, 2020. http://hdl.handle.net/2142/106162.

MLA Handbook (7th Edition):

Radaideh, Majdi Ibrahim Ahmad. “A novel framework for data-driven modeling, uncertainty quantification, and deep learning of nuclear reactor simulations.” 2019. Web. 27 Sep 2020.

Vancouver:

Radaideh MIA. A novel framework for data-driven modeling, uncertainty quantification, and deep learning of nuclear reactor simulations. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2019. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/2142/106162.

Council of Science Editors:

Radaideh MIA. A novel framework for data-driven modeling, uncertainty quantification, and deep learning of nuclear reactor simulations. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2019. Available from: http://hdl.handle.net/2142/106162


University of South Carolina

29. Fowler, Jay Louis. Communicating the Certainty of Data Cartographically.

Degree: MS, Geography, 2011, University of South Carolina

  People seeking information to guide their learning, understanding, and decision-making frequently come into contact with data of varying degrees of reliability. This is unavoidable… (more)

Subjects/Keywords: Geography; Social and Behavioral Sciences; Cartography; Data certainty; Drought; Uncertainty; Visualization

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APA (6th Edition):

Fowler, J. L. (2011). Communicating the Certainty of Data Cartographically. (Masters Thesis). University of South Carolina. Retrieved from https://scholarcommons.sc.edu/etd/1283

Chicago Manual of Style (16th Edition):

Fowler, Jay Louis. “Communicating the Certainty of Data Cartographically.” 2011. Masters Thesis, University of South Carolina. Accessed September 27, 2020. https://scholarcommons.sc.edu/etd/1283.

MLA Handbook (7th Edition):

Fowler, Jay Louis. “Communicating the Certainty of Data Cartographically.” 2011. Web. 27 Sep 2020.

Vancouver:

Fowler JL. Communicating the Certainty of Data Cartographically. [Internet] [Masters thesis]. University of South Carolina; 2011. [cited 2020 Sep 27]. Available from: https://scholarcommons.sc.edu/etd/1283.

Council of Science Editors:

Fowler JL. Communicating the Certainty of Data Cartographically. [Masters Thesis]. University of South Carolina; 2011. Available from: https://scholarcommons.sc.edu/etd/1283


University of Manchester

30. Sanchez Serrano, Fernando Rene. A probabilistic approach to uncertainty quantification in pay-as-you-go data integration.

Degree: PhD, 2019, University of Manchester

 The use of Web standards, compact publication guidelines, and open data initiatives have motivated many public and private organisations to publish data on the Web,… (more)

Subjects/Keywords: 004; data integration; pay as you go; probabilistic approach; uncertainty quantification

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APA (6th Edition):

Sanchez Serrano, F. R. (2019). A probabilistic approach to uncertainty quantification in pay-as-you-go data integration. (Doctoral Dissertation). University of Manchester. Retrieved from https://www.research.manchester.ac.uk/portal/en/theses/a-probabilistic-approach-to-uncertainty-quantification-in-payasyougo-data-integration(31bcad79-5892-4a23-9534-f5caf5b6546b).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.791245

Chicago Manual of Style (16th Edition):

Sanchez Serrano, Fernando Rene. “A probabilistic approach to uncertainty quantification in pay-as-you-go data integration.” 2019. Doctoral Dissertation, University of Manchester. Accessed September 27, 2020. https://www.research.manchester.ac.uk/portal/en/theses/a-probabilistic-approach-to-uncertainty-quantification-in-payasyougo-data-integration(31bcad79-5892-4a23-9534-f5caf5b6546b).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.791245.

MLA Handbook (7th Edition):

Sanchez Serrano, Fernando Rene. “A probabilistic approach to uncertainty quantification in pay-as-you-go data integration.” 2019. Web. 27 Sep 2020.

Vancouver:

Sanchez Serrano FR. A probabilistic approach to uncertainty quantification in pay-as-you-go data integration. [Internet] [Doctoral dissertation]. University of Manchester; 2019. [cited 2020 Sep 27]. Available from: https://www.research.manchester.ac.uk/portal/en/theses/a-probabilistic-approach-to-uncertainty-quantification-in-payasyougo-data-integration(31bcad79-5892-4a23-9534-f5caf5b6546b).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.791245.

Council of Science Editors:

Sanchez Serrano FR. A probabilistic approach to uncertainty quantification in pay-as-you-go data integration. [Doctoral Dissertation]. University of Manchester; 2019. Available from: https://www.research.manchester.ac.uk/portal/en/theses/a-probabilistic-approach-to-uncertainty-quantification-in-payasyougo-data-integration(31bcad79-5892-4a23-9534-f5caf5b6546b).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.791245

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