Neural Network Algorithms and Their Engineering Applications
Morgan Kaufmann Publishers In (Verlag)
978-0-443-29202-6 (ISBN)
- Noch nicht erschienen (ca. April 2025)
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The authors provide a deep discussion for the potential application of machine learning methods in improving the optimization performance of the neural network algorithm, helping readers understand how to use machine learning methods to design improved versions of the algorithm. Users will find a wealth of source code that covers all applied algorithms. Code applications enhance readers' understanding of methods covered and facilitate readers' ability to apply the algorithms to their own research and development projects.
Dr. Chao Huang received the B.Sc. degree in automation, from China University of Petroleum, Beijing, China, in June 2012, and received Ph.D degree from the University of Wollongong, Australia, in Dec. 2018. From Sep. 2018 to Sep. 2019, she worked as a project leader at National Institute of Informatics, Tokyo, Japan. From Oct. 2019 to July 2021, she worked as a postdoctoral research fellow at the School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore. She is now a research assistant professor at the Department of Industrial and Systems Engineering, the Hong Kong Polytechnic University, Hong Kong. Her interests include motion planning, human machine collaboration, fault tolerant, and automotive control and application. Dr. Hailong Huang received a B.Sc. degree in automation, from China University of Petroleum, Beijing, China, in June 2012, and received Ph.D degree in Systems and Control from the University of New South Wales, Sydney, Australia, in March 2018. From Feb. 2018 to July 2021, he worked as a postdoctoral research fellow at the School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, Australia. He is now an assistant professor at the Department of Aeronautical and Aviation Engineering, the Hong Kong Polytechnic University. His current research interests include the coordination, navigation and control of ground robots and unmanned aerial vehicles. Dr Yiying ZHANG received the B.S. degree from Yanshan University, Qinhuangdao, China, in 2014, the M.S. degree from Harbin Institute of Technology, Harbin, China, in 2016, and the Ph.D. degree from Tianjin University, Tianjin, China, in 2021, all in information and communication engineering. He is currently a postdoctoral fellow of the Hong Kong Polytechnic University. His research interests include machine learning, evolutionary computation, and path planning of unmanned aerial vehicles.
1. Introduction
2. Neural network algorithm
3. Constrained engineering design optimization problems
4. Parameter estimation of proton exchange membrane fuel cell models
5. Parameter extraction of photovoltaic models
6. Discussion on the applications of machine learning methods in neural network algorithm
7. Conclusion
| Erscheint lt. Verlag | 1.4.2025 |
|---|---|
| Verlagsort | San Francisco |
| Sprache | englisch |
| Maße | 191 x 235 mm |
| Themenwelt | Informatik ► Theorie / Studium ► Algorithmen |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Informatik ► Weitere Themen ► Bioinformatik | |
| ISBN-10 | 0-443-29202-7 / 0443292027 |
| ISBN-13 | 978-0-443-29202-6 / 9780443292026 |
| Zustand | Neuware |
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