The Development of NNFLC Hybrid System, Based on Fuzzy and Neural Approach for MatLab

Student: Sadekova Tasnima

Supervisor: Dmitry Bogolyubov

Faculty: HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE)

Educational Programme: Information Systems and Technology (Bachelor)

Final Grade: 9

Year of Graduation: 2016

In this work hybrid systems, which combine fuzzy logic and neural networks, are studied. The main purpose is to develop fuzzy neural network NNFLC in MATLAB. The feature of this system is that it can be constructed from training data by machine learning techniques and it uses learning ability of neural networks to develop fuzzy logic rules and find optimal parameters of input/output membership functions. Also it combines two learning mechanisms: unsupervised (self-organized) and supervised, what allows to increase learning speed. Programming realization of this network allows to solve different objectives, for example, clustering, regression analysis.

Full text (added May 28, 2016)

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