2- Course Aim

The aim of this course is to introduce various types of fuzzy inference systems, neural networks, and genetic algorithms, along with several synergistic approaches for combining them, including neuro and fuzzy techniques, neuro-fuzzy models, the use of neural models in fuzzy systems design, genetic auto-tuning techniques, genetic training of neural nets, fuzzified neural nets, and neural genetic fuzzy models. Naturally, with so many new approaches developing in this field, it is possible in an entry-level graduate course only to cover the main topics in depth and to offer only a general overview on the more advanced hybrid approaches. The purpose of this course is to allow students to pursue these advanced approaches to a much greater depth. The emphasis will be on applications, including modeling, prediction, design, control, databases, and data mining, just as is already the case in the previous course.