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You searched for subject:(Unscented transformation). Showing records 1 – 6 of 6 total matches.

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Universidade Nova

1. Oliveira, Tiago Miguel Brites. Recursive neuro fuzzy techniques for online identification and control.

Degree: 2013, Universidade Nova

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

The main goal of this thesis will be focused on developing an… (more)

Subjects/Keywords: Recursive optimization; Online identification; Adaptative control; Self learning; Kalman filtering; Unscented transformation

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

APA (6th Edition):

Oliveira, T. M. B. (2013). Recursive neuro fuzzy techniques for online identification and control. (Thesis). Universidade Nova. Retrieved from http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/10552

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):

Oliveira, Tiago Miguel Brites. “Recursive neuro fuzzy techniques for online identification and control.” 2013. Thesis, Universidade Nova. Accessed April 18, 2021. http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/10552.

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

MLA Handbook (7th Edition):

Oliveira, Tiago Miguel Brites. “Recursive neuro fuzzy techniques for online identification and control.” 2013. Web. 18 Apr 2021.

Vancouver:

Oliveira TMB. Recursive neuro fuzzy techniques for online identification and control. [Internet] [Thesis]. Universidade Nova; 2013. [cited 2021 Apr 18]. Available from: http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/10552.

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

Council of Science Editors:

Oliveira TMB. Recursive neuro fuzzy techniques for online identification and control. [Thesis]. Universidade Nova; 2013. Available from: http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/10552

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

2. Qiao, Chenxi. Unscented Transformation-based Probabilistic Optimal Power Flow.

Degree: 2015, University of Nevada – Reno

 Renewable energy-based generation causes uncertainties in power system operation and planning due to its stochastic nature. The load uncertainties combined with the increasing penetration of… (more)

Subjects/Keywords: locational marginal price; probabilistic optimal power flow; probabilistic power flow; unscented transformation

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APA (6th Edition):

Qiao, C. (2015). Unscented Transformation-based Probabilistic Optimal Power Flow. (Thesis). University of Nevada – Reno. Retrieved from http://hdl.handle.net/11714/2679

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):

Qiao, Chenxi. “Unscented Transformation-based Probabilistic Optimal Power Flow.” 2015. Thesis, University of Nevada – Reno. Accessed April 18, 2021. http://hdl.handle.net/11714/2679.

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

MLA Handbook (7th Edition):

Qiao, Chenxi. “Unscented Transformation-based Probabilistic Optimal Power Flow.” 2015. Web. 18 Apr 2021.

Vancouver:

Qiao C. Unscented Transformation-based Probabilistic Optimal Power Flow. [Internet] [Thesis]. University of Nevada – Reno; 2015. [cited 2021 Apr 18]. Available from: http://hdl.handle.net/11714/2679.

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

Council of Science Editors:

Qiao C. Unscented Transformation-based Probabilistic Optimal Power Flow. [Thesis]. University of Nevada – Reno; 2015. Available from: http://hdl.handle.net/11714/2679

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


Penn State University

3. Hall, Zachary Joseph. Higher Order Polynomial Approximation For Applications in Space Situational Awareness.

Degree: 2018, Penn State University

 The uncertain Lambert problem and computation of reachability sets are in many ways complimentary problems with important applications in Space Situational Awareness (SSA). Formulating the… (more)

Subjects/Keywords: space situational awareness; conjugate unscented transformation; polynomial approximation; higher order sensitivity; uncertain lambert problem; reachability sets

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APA (6th Edition):

Hall, Z. J. (2018). Higher Order Polynomial Approximation For Applications in Space Situational Awareness. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/16061zyh5059

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):

Hall, Zachary Joseph. “Higher Order Polynomial Approximation For Applications in Space Situational Awareness.” 2018. Thesis, Penn State University. Accessed April 18, 2021. https://submit-etda.libraries.psu.edu/catalog/16061zyh5059.

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

MLA Handbook (7th Edition):

Hall, Zachary Joseph. “Higher Order Polynomial Approximation For Applications in Space Situational Awareness.” 2018. Web. 18 Apr 2021.

Vancouver:

Hall ZJ. Higher Order Polynomial Approximation For Applications in Space Situational Awareness. [Internet] [Thesis]. Penn State University; 2018. [cited 2021 Apr 18]. Available from: https://submit-etda.libraries.psu.edu/catalog/16061zyh5059.

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

Council of Science Editors:

Hall ZJ. Higher Order Polynomial Approximation For Applications in Space Situational Awareness. [Thesis]. Penn State University; 2018. Available from: https://submit-etda.libraries.psu.edu/catalog/16061zyh5059

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


University of New Orleans

4. Li, Yi. Application of Monte Carlo (MC) method and Unscented Transformation (UT) method into Trajectory Prediction of a Dropped Cylinder in Two Dimensions.

Degree: MS, Naval Architecture and Marine Engineering, 2020, University of New Orleans

  Monte Carlo (MC) method is one of the commonly used methods to study stochastic statistical problems in the field of marine engineering. There is… (more)

Subjects/Keywords: Trajectory prediction, Dropped cylinders, State space model, Offshore operations, Monte Carlo method, Unscented transformation method; Other Engineering

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

APA (6th Edition):

Li, Y. (2020). Application of Monte Carlo (MC) method and Unscented Transformation (UT) method into Trajectory Prediction of a Dropped Cylinder in Two Dimensions. (Thesis). University of New Orleans. Retrieved from https://scholarworks.uno.edu/td/2783

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):

Li, Yi. “Application of Monte Carlo (MC) method and Unscented Transformation (UT) method into Trajectory Prediction of a Dropped Cylinder in Two Dimensions.” 2020. Thesis, University of New Orleans. Accessed April 18, 2021. https://scholarworks.uno.edu/td/2783.

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

MLA Handbook (7th Edition):

Li, Yi. “Application of Monte Carlo (MC) method and Unscented Transformation (UT) method into Trajectory Prediction of a Dropped Cylinder in Two Dimensions.” 2020. Web. 18 Apr 2021.

Vancouver:

Li Y. Application of Monte Carlo (MC) method and Unscented Transformation (UT) method into Trajectory Prediction of a Dropped Cylinder in Two Dimensions. [Internet] [Thesis]. University of New Orleans; 2020. [cited 2021 Apr 18]. Available from: https://scholarworks.uno.edu/td/2783.

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

Council of Science Editors:

Li Y. Application of Monte Carlo (MC) method and Unscented Transformation (UT) method into Trajectory Prediction of a Dropped Cylinder in Two Dimensions. [Thesis]. University of New Orleans; 2020. Available from: https://scholarworks.uno.edu/td/2783

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

5. Hu, Junjun. Forecast Uncertainty Quantification using Monte Carlo, Polynomial Chaos Expansion and Unscented Transformation Methods.

Degree: PhD, 2015, University of Oklahoma

 In the context of prediction science, the sources of uncertainty can be from the uncertainties of the experiments, modeling, model inputs, numerical analysis, etc. This… (more)

Subjects/Keywords: Uncertainty Quantification; Polynomial Chaos Expansion; Unscented Transformation

…90 Chapter 6 Application of Unscented Transformation Approach… …131 Appendix D Performance of Unscented Transformation… …138 Appendix E Performance of Scaled Unscented Transformation… …unscented transformation (UT). Using MC as the benchmark, two dynamical models are used… …extent, further efforts are still needed. The unscented transformation (UT) method is… 

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

APA (6th Edition):

Hu, J. (2015). Forecast Uncertainty Quantification using Monte Carlo, Polynomial Chaos Expansion and Unscented Transformation Methods. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/21722

Chicago Manual of Style (16th Edition):

Hu, Junjun. “Forecast Uncertainty Quantification using Monte Carlo, Polynomial Chaos Expansion and Unscented Transformation Methods.” 2015. Doctoral Dissertation, University of Oklahoma. Accessed April 18, 2021. http://hdl.handle.net/11244/21722.

MLA Handbook (7th Edition):

Hu, Junjun. “Forecast Uncertainty Quantification using Monte Carlo, Polynomial Chaos Expansion and Unscented Transformation Methods.” 2015. Web. 18 Apr 2021.

Vancouver:

Hu J. Forecast Uncertainty Quantification using Monte Carlo, Polynomial Chaos Expansion and Unscented Transformation Methods. [Internet] [Doctoral dissertation]. University of Oklahoma; 2015. [cited 2021 Apr 18]. Available from: http://hdl.handle.net/11244/21722.

Council of Science Editors:

Hu J. Forecast Uncertainty Quantification using Monte Carlo, Polynomial Chaos Expansion and Unscented Transformation Methods. [Doctoral Dissertation]. University of Oklahoma; 2015. Available from: http://hdl.handle.net/11244/21722


Virginia Tech

6. Zhao, Junbo. A Robust Dynamic State and Parameter Estimation Framework for Smart Grid Monitoring and Control.

Degree: PhD, Electrical Engineering, 2018, Virginia Tech

 The enhancement of the reliability, security, and resiliency of electric power systems depends on the availability of fast, accurate, and robust dynamic state estimators. These… (more)

Subjects/Keywords: Kalman filter; Robust statistics; Power system state estimation; Dynamic state estimation; Unscented transformation; Robust control theory; Estimation theory; Power system dynamics and control; Outliers; Cyber attacks; Phasor measurement units

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

APA (6th Edition):

Zhao, J. (2018). A Robust Dynamic State and Parameter Estimation Framework for Smart Grid Monitoring and Control. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/83423

Chicago Manual of Style (16th Edition):

Zhao, Junbo. “A Robust Dynamic State and Parameter Estimation Framework for Smart Grid Monitoring and Control.” 2018. Doctoral Dissertation, Virginia Tech. Accessed April 18, 2021. http://hdl.handle.net/10919/83423.

MLA Handbook (7th Edition):

Zhao, Junbo. “A Robust Dynamic State and Parameter Estimation Framework for Smart Grid Monitoring and Control.” 2018. Web. 18 Apr 2021.

Vancouver:

Zhao J. A Robust Dynamic State and Parameter Estimation Framework for Smart Grid Monitoring and Control. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2021 Apr 18]. Available from: http://hdl.handle.net/10919/83423.

Council of Science Editors:

Zhao J. A Robust Dynamic State and Parameter Estimation Framework for Smart Grid Monitoring and Control. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/83423

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