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You searched for +publisher:"University of Ontario Institute of Technology" +contributor:("Rahnamayan, Shahryar"). Showing records 1 – 10 of 10 total matches.

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University of Ontario Institute of Technology

1. Esmailzadeh, Ali. Novel opposition-based sampling methods for efficiently solving challenging optimization problems.

Degree: 2011, University of Ontario Institute of Technology

 In solving noise-free and noisy optimization problems, candidate initialization and sampling play a key role, but are not deeply investigated. It is of interest to… (more)

Subjects/Keywords: Opposition-based learning; Large-scale; Noisy; Sampling methods; Evolutionary algorithm

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APA (6th Edition):

Esmailzadeh, A. (2011). Novel opposition-based sampling methods for efficiently solving challenging optimization problems. (Thesis). University of Ontario Institute of Technology. Retrieved from http://hdl.handle.net/10155/150

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):

Esmailzadeh, Ali. “Novel opposition-based sampling methods for efficiently solving challenging optimization problems.” 2011. Thesis, University of Ontario Institute of Technology. Accessed February 22, 2019. http://hdl.handle.net/10155/150.

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

MLA Handbook (7th Edition):

Esmailzadeh, Ali. “Novel opposition-based sampling methods for efficiently solving challenging optimization problems.” 2011. Web. 22 Feb 2019.

Vancouver:

Esmailzadeh A. Novel opposition-based sampling methods for efficiently solving challenging optimization problems. [Internet] [Thesis]. University of Ontario Institute of Technology; 2011. [cited 2019 Feb 22]. Available from: http://hdl.handle.net/10155/150.

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

Council of Science Editors:

Esmailzadeh A. Novel opposition-based sampling methods for efficiently solving challenging optimization problems. [Thesis]. University of Ontario Institute of Technology; 2011. Available from: http://hdl.handle.net/10155/150

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


University of Ontario Institute of Technology

2. Darvish, Arman. User aid-based evolutionary computation for optimal parameter setting of image enhancement and segmentation.

Degree: 2011, University of Ontario Institute of Technology

 Applications of imaging and image processing become a part of our daily life and find their crucial way in real-world areas. Accordingly, the corresponding techniques… (more)

Subjects/Keywords: Image processing; Segmentation; Optimization; Image enhancement

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

APA (6th Edition):

Darvish, A. (2011). User aid-based evolutionary computation for optimal parameter setting of image enhancement and segmentation. (Thesis). University of Ontario Institute of Technology. Retrieved from http://hdl.handle.net/10155/209

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):

Darvish, Arman. “User aid-based evolutionary computation for optimal parameter setting of image enhancement and segmentation.” 2011. Thesis, University of Ontario Institute of Technology. Accessed February 22, 2019. http://hdl.handle.net/10155/209.

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

MLA Handbook (7th Edition):

Darvish, Arman. “User aid-based evolutionary computation for optimal parameter setting of image enhancement and segmentation.” 2011. Web. 22 Feb 2019.

Vancouver:

Darvish A. User aid-based evolutionary computation for optimal parameter setting of image enhancement and segmentation. [Internet] [Thesis]. University of Ontario Institute of Technology; 2011. [cited 2019 Feb 22]. Available from: http://hdl.handle.net/10155/209.

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

Council of Science Editors:

Darvish A. User aid-based evolutionary computation for optimal parameter setting of image enhancement and segmentation. [Thesis]. University of Ontario Institute of Technology; 2011. Available from: http://hdl.handle.net/10155/209

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


University of Ontario Institute of Technology

3. Shahbazpanahi, Shaho. Learning image enhancement and object localization using evolutionary algorithms.

Degree: 2014, University of Ontario Institute of Technology

 Imaging and image processing have been used in variety of applications, such as medical, astronomy, forensic, and industry. Numerous techniques have been proposed to solve… (more)

Subjects/Keywords: Hybrid GP-DE; Learning image enhancement

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APA (6th Edition):

Shahbazpanahi, S. (2014). Learning image enhancement and object localization using evolutionary algorithms. (Thesis). University of Ontario Institute of Technology. Retrieved from http://hdl.handle.net/10155/424

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):

Shahbazpanahi, Shaho. “Learning image enhancement and object localization using evolutionary algorithms.” 2014. Thesis, University of Ontario Institute of Technology. Accessed February 22, 2019. http://hdl.handle.net/10155/424.

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

MLA Handbook (7th Edition):

Shahbazpanahi, Shaho. “Learning image enhancement and object localization using evolutionary algorithms.” 2014. Web. 22 Feb 2019.

Vancouver:

Shahbazpanahi S. Learning image enhancement and object localization using evolutionary algorithms. [Internet] [Thesis]. University of Ontario Institute of Technology; 2014. [cited 2019 Feb 22]. Available from: http://hdl.handle.net/10155/424.

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

Council of Science Editors:

Shahbazpanahi S. Learning image enhancement and object localization using evolutionary algorithms. [Thesis]. University of Ontario Institute of Technology; 2014. Available from: http://hdl.handle.net/10155/424

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


University of Ontario Institute of Technology

4. Mohamad, Zaid. Tissue segmentation using medical image processing chain optimization.

Degree: 2016, University of Ontario Institute of Technology

 Surveyed literature shows many segmentation algorithms using different types of optimization methods. These methods were used to minimize or maximize objective functions of entropy, similarity,… (more)

Subjects/Keywords: Segmentation; Image processing chain; Differential evolution

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APA (6th Edition):

Mohamad, Z. (2016). Tissue segmentation using medical image processing chain optimization. (Thesis). University of Ontario Institute of Technology. Retrieved from http://hdl.handle.net/10155/697

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):

Mohamad, Zaid. “Tissue segmentation using medical image processing chain optimization.” 2016. Thesis, University of Ontario Institute of Technology. Accessed February 22, 2019. http://hdl.handle.net/10155/697.

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

MLA Handbook (7th Edition):

Mohamad, Zaid. “Tissue segmentation using medical image processing chain optimization.” 2016. Web. 22 Feb 2019.

Vancouver:

Mohamad Z. Tissue segmentation using medical image processing chain optimization. [Internet] [Thesis]. University of Ontario Institute of Technology; 2016. [cited 2019 Feb 22]. Available from: http://hdl.handle.net/10155/697.

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

Council of Science Editors:

Mohamad Z. Tissue segmentation using medical image processing chain optimization. [Thesis]. University of Ontario Institute of Technology; 2016. Available from: http://hdl.handle.net/10155/697

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


University of Ontario Institute of Technology

5. Alfughi, Zakiya. Optimal farm design with parabolic shape photovoltaic panels using multi-objective optimization.

Degree: 2015, University of Ontario Institute of Technology

 To acquire the maximum efficiency for solar electricity conversion, a solar panel has to absorb nearly every single photon of light emitted from the sun.… (more)

Subjects/Keywords: Photovoltaic; Parabolic trough panel; Multi-objective optimization

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APA (6th Edition):

Alfughi, Z. (2015). Optimal farm design with parabolic shape photovoltaic panels using multi-objective optimization. (Thesis). University of Ontario Institute of Technology. Retrieved from http://hdl.handle.net/10155/548

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):

Alfughi, Zakiya. “Optimal farm design with parabolic shape photovoltaic panels using multi-objective optimization.” 2015. Thesis, University of Ontario Institute of Technology. Accessed February 22, 2019. http://hdl.handle.net/10155/548.

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

MLA Handbook (7th Edition):

Alfughi, Zakiya. “Optimal farm design with parabolic shape photovoltaic panels using multi-objective optimization.” 2015. Web. 22 Feb 2019.

Vancouver:

Alfughi Z. Optimal farm design with parabolic shape photovoltaic panels using multi-objective optimization. [Internet] [Thesis]. University of Ontario Institute of Technology; 2015. [cited 2019 Feb 22]. Available from: http://hdl.handle.net/10155/548.

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

Council of Science Editors:

Alfughi Z. Optimal farm design with parabolic shape photovoltaic panels using multi-objective optimization. [Thesis]. University of Ontario Institute of Technology; 2015. Available from: http://hdl.handle.net/10155/548

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


University of Ontario Institute of Technology

6. Rabbani, Hassan. Modeling and multi-objective optimization of a photovoltaic-thermal based multigeneration system.

Degree: 2015, University of Ontario Institute of Technology

 In this thesis, a novel multi generation integrated system is introduced, analyzed and optimized. It consists of GaAs based PV (Photo-Voltaic) arrays connected in series.… (more)

Subjects/Keywords: Solar energy; Photovoltaics; PVT systems; Optimization; Energy

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APA (6th Edition):

Rabbani, H. (2015). Modeling and multi-objective optimization of a photovoltaic-thermal based multigeneration system. (Thesis). University of Ontario Institute of Technology. Retrieved from http://hdl.handle.net/10155/612

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):

Rabbani, Hassan. “Modeling and multi-objective optimization of a photovoltaic-thermal based multigeneration system.” 2015. Thesis, University of Ontario Institute of Technology. Accessed February 22, 2019. http://hdl.handle.net/10155/612.

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

MLA Handbook (7th Edition):

Rabbani, Hassan. “Modeling and multi-objective optimization of a photovoltaic-thermal based multigeneration system.” 2015. Web. 22 Feb 2019.

Vancouver:

Rabbani H. Modeling and multi-objective optimization of a photovoltaic-thermal based multigeneration system. [Internet] [Thesis]. University of Ontario Institute of Technology; 2015. [cited 2019 Feb 22]. Available from: http://hdl.handle.net/10155/612.

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

Council of Science Editors:

Rabbani H. Modeling and multi-objective optimization of a photovoltaic-thermal based multigeneration system. [Thesis]. University of Ontario Institute of Technology; 2015. Available from: http://hdl.handle.net/10155/612

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


University of Ontario Institute of Technology

7. Gillett, Jonathan. Predicting Bitcoin: a robust model for predicting Bitcoin price directions based on network influencers.

Degree: 2016, University of Ontario Institute of Technology

 The ability to predict financial markets has tremendous potential to limit exposure to risk and provide better assurances of annualized gains. In this thesis, a… (more)

Subjects/Keywords: Bitcoin; Predictive model; Machine learning

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APA (6th Edition):

Gillett, J. (2016). Predicting Bitcoin: a robust model for predicting Bitcoin price directions based on network influencers. (Thesis). University of Ontario Institute of Technology. Retrieved from http://hdl.handle.net/10155/884

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):

Gillett, Jonathan. “Predicting Bitcoin: a robust model for predicting Bitcoin price directions based on network influencers.” 2016. Thesis, University of Ontario Institute of Technology. Accessed February 22, 2019. http://hdl.handle.net/10155/884.

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

MLA Handbook (7th Edition):

Gillett, Jonathan. “Predicting Bitcoin: a robust model for predicting Bitcoin price directions based on network influencers.” 2016. Web. 22 Feb 2019.

Vancouver:

Gillett J. Predicting Bitcoin: a robust model for predicting Bitcoin price directions based on network influencers. [Internet] [Thesis]. University of Ontario Institute of Technology; 2016. [cited 2019 Feb 22]. Available from: http://hdl.handle.net/10155/884.

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

Council of Science Editors:

Gillett J. Predicting Bitcoin: a robust model for predicting Bitcoin price directions based on network influencers. [Thesis]. University of Ontario Institute of Technology; 2016. Available from: http://hdl.handle.net/10155/884

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


University of Ontario Institute of Technology

8. Bourennani, Farid. Leadership based multi-objective optimization with applications in energy systems.

Degree: 2013, University of Ontario Institute of Technology

 Multi-objective optimization metaheuristics (MOMs) are powerful methods for solving complex optimization problems but can require a large number of function evaluations to find optimal solutions.… (more)

Subjects/Keywords: Multi-objective optimization; Multiobjective evolutionary computation; Metaheuristics; Hybrid energy systems design

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APA (6th Edition):

Bourennani, F. (2013). Leadership based multi-objective optimization with applications in energy systems. (Thesis). University of Ontario Institute of Technology. Retrieved from http://hdl.handle.net/10155/396

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):

Bourennani, Farid. “Leadership based multi-objective optimization with applications in energy systems.” 2013. Thesis, University of Ontario Institute of Technology. Accessed February 22, 2019. http://hdl.handle.net/10155/396.

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

MLA Handbook (7th Edition):

Bourennani, Farid. “Leadership based multi-objective optimization with applications in energy systems.” 2013. Web. 22 Feb 2019.

Vancouver:

Bourennani F. Leadership based multi-objective optimization with applications in energy systems. [Internet] [Thesis]. University of Ontario Institute of Technology; 2013. [cited 2019 Feb 22]. Available from: http://hdl.handle.net/10155/396.

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

Council of Science Editors:

Bourennani F. Leadership based multi-objective optimization with applications in energy systems. [Thesis]. University of Ontario Institute of Technology; 2013. Available from: http://hdl.handle.net/10155/396

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


University of Ontario Institute of Technology

9. Salehinejad, Hojjat. Micro-differential evolution: diversity enhancement and comparative study.

Degree: 2014, University of Ontario Institute of Technology

 Evolutionary algorithms (EAs), such as the differential evolution (DE) algorithm, suffer from high computational time due to large population size and nature of evaluation, to… (more)

Subjects/Keywords: Diversity; Evolutionary algorithms; Micro-differential evolution; Comparative study

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APA (6th Edition):

Salehinejad, H. (2014). Micro-differential evolution: diversity enhancement and comparative study. (Thesis). University of Ontario Institute of Technology. Retrieved from http://hdl.handle.net/10155/459

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):

Salehinejad, Hojjat. “Micro-differential evolution: diversity enhancement and comparative study.” 2014. Thesis, University of Ontario Institute of Technology. Accessed February 22, 2019. http://hdl.handle.net/10155/459.

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

MLA Handbook (7th Edition):

Salehinejad, Hojjat. “Micro-differential evolution: diversity enhancement and comparative study.” 2014. Web. 22 Feb 2019.

Vancouver:

Salehinejad H. Micro-differential evolution: diversity enhancement and comparative study. [Internet] [Thesis]. University of Ontario Institute of Technology; 2014. [cited 2019 Feb 22]. Available from: http://hdl.handle.net/10155/459.

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

Council of Science Editors:

Salehinejad H. Micro-differential evolution: diversity enhancement and comparative study. [Thesis]. University of Ontario Institute of Technology; 2014. Available from: http://hdl.handle.net/10155/459

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


University of Ontario Institute of Technology

10. Ibrahim, Amin. Toward enhancement of evolutionary multi- and many-objective optimization: algorithms, performance metrics, and visualization techniques.

Degree: 2017, University of Ontario Institute of Technology

 In the last three decades, the focus of multi-criteria optimization has been solving problems containing two or three objectives. However, real-world problems generally involve multiple… (more)

Subjects/Keywords: Many-objective optimization; Visualization; Performance metrics; Hybrid optimization; Evolutionary computation

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APA (6th Edition):

Ibrahim, A. (2017). Toward enhancement of evolutionary multi- and many-objective optimization: algorithms, performance metrics, and visualization techniques. (Thesis). University of Ontario Institute of Technology. Retrieved from http://hdl.handle.net/10155/882

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):

Ibrahim, Amin. “Toward enhancement of evolutionary multi- and many-objective optimization: algorithms, performance metrics, and visualization techniques.” 2017. Thesis, University of Ontario Institute of Technology. Accessed February 22, 2019. http://hdl.handle.net/10155/882.

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

MLA Handbook (7th Edition):

Ibrahim, Amin. “Toward enhancement of evolutionary multi- and many-objective optimization: algorithms, performance metrics, and visualization techniques.” 2017. Web. 22 Feb 2019.

Vancouver:

Ibrahim A. Toward enhancement of evolutionary multi- and many-objective optimization: algorithms, performance metrics, and visualization techniques. [Internet] [Thesis]. University of Ontario Institute of Technology; 2017. [cited 2019 Feb 22]. Available from: http://hdl.handle.net/10155/882.

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

Council of Science Editors:

Ibrahim A. Toward enhancement of evolutionary multi- and many-objective optimization: algorithms, performance metrics, and visualization techniques. [Thesis]. University of Ontario Institute of Technology; 2017. Available from: http://hdl.handle.net/10155/882

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

.