Adv Topics Applied Soft Compu

Course Description

Course is designed to follow a currently offered course, SSIE 519: Applied Soft Computing. Both courses are designed to cover relatively new approaches to machine intelligence and systems analysis known collectively as soft computing. The 519 course already introduces 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 SSIE 616 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 519 course. Prerequisite: SSIE 519. Offered in the Spring semester. 3 credits.

Code

SSIE 616

Credits

3

Subject

SSIE

Programs That Include This Course

• Graduate Certificate Graduate Certificate in Complex Systems Science and Engineering
• Master's Master of Science in Industrial and Systems Engineering
• Master's Master of Science in Systems Science