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This is an interdisciplinary course on AI. It can be helpful for all graduate students who would like to use intelligent systems in their research. |
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In this course, we review the main components of soft computing including fuzzy logic, neural networks, and genetic algorithms. This course should help graduate students use these components and their combinations in their current and future projects. The general theme of the course is how soft computing can serve human society and solve its many ailments. In particular, we are concerned with helping the disabled and poverty |
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Having completed at least one of the introductory courses on intelligent systems, such as fuzzy logic, neural networks, or evolutionary algorithms. |
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This course is designed as a research seminar course. The first half, it is more similar to a conventional lecture sessions using powerpoint presentations, while the student seminar and class discussions will make up most of the second half. |
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class presentations, partipate in class discussions, answer the research questions at the end of each lecture, complete homework, final project, and final exam. |
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１. Neuro-Fuzzy and Soft Computing*, by Jang, Sun and Mizutani, Matlab Curriculum Series, Prentice Hall, 1997.
2. Four Class DVDs include my presentations, electronic library of books, proceedings of the WCCI’16, WCCI’14, WCCI’12, WCCI’10, WCCI’08, WCCI’06, IEEE-CEC07, plus other resources. |
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Internet, Powerpoint Presentations, MS Word |
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Exams - 6 Points
Homework - 4 Points
Final Project - 6 Points
Class Presentations (Group) - 4 Points |
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The skills to synergistically design new paradigms of intelligent systems to solve difficult/complex/uncertain engineering problems.. |
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Pdf File |