000			02549nmm a2200373Ia 4500
001			00002225
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007			cr |uu|||uu|||
008			181207s1994 si a ob 001 0 eng d
010			_z 95122858
040			_aWSPC _beng _cWSPC
020			_a9789814354240 _q(ebook)
020			_z9789810216139 _q(hbk.)
050	0	4	_aTJ217.5 _b.L56 1994
072		7	_aTEC _x000000 _2bisacsh
072		7	_aTEC _x009030 _2bisacsh
082	0	4	_a629.8 _223
100	1		_aLin, C. T. _q(Ching Tai), _d1944- _93411
245	1	0	_aNeural fuzzy control systems with structure and parameter learning _h[electronic resource] / _cC.T. Lin ; foreword by C.S. George Lee.
260			_aSingapore : _bWorld Scientific Publishing Co. Pte Ltd., _c©1994.
300			_a1 online resource (144 p.) : _bill.
538			_aSystem requirements: Adobe Acrobat Reader.
538			_aMode of access: World Wide Web.
588			_aTitle from web page (viewed December 7, 2018).
504			_aIncludes bibliographical references (p. 117-123) and index.
520			_a"A general neural-network-based connectionist model, called Fuzzy Neural Network (FNN), is proposed in this book for the realization of a fuzzy logic control and decision system. The FNN is a feedforward multi-layered network which integrates the basic elements and functions of a traditional fuzzy logic controller into a connectionist structure which has distributed learning abilities. In order to set up this proposed FNN, the author recommends two complementary structure/parameter learning algorithms: a two-phase hybrid learning algorithm and an on-line supervised structure/parameter learning algorithm. Both of these learning algorithms require exact supervised training data for learning. In some real-time applications, exact training data may be expensive or even impossible to get. To solve this reinforcement learning problem for real-world applications, a Reinforcement Fuzzy Neural Network (RFNN) is further proposed. Computer simulation examples are presented to illustrate the performance and applicability of the proposed FNN, RFNN and their associated learning algorithms for various applications."-- _cPublisher's website.
650		0	_aIntelligent control systems. _93412
650		0	_aFuzzy systems. _93413
650		0	_aNeural networks (Computer science) _93414
650		0	_aElectronic books. _920548
856	4	0	_uhttps://www.worldscientific.com/worldscibooks/10.1142/2225#t=toc _zAccess to full text is restricted to subscribers.
942			_cEBK
999			_c72431 _d72431