Proceedings of 1995 IEEE International Conference on Fuzzy Systems: The International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and the Second International Fuzzy Engineering Symposium : March 20-24, 1995, Yokohama, Japan, Volume 3 |
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Page 1122
... degree , ie . how much a pixel context resembles to class i required context . This realisation degree is a number belonging to the [ -1 , + 1 ] interval . principally slope orientation oflen . elevation Dever Fuzzy neural network for ...
... degree , ie . how much a pixel context resembles to class i required context . This realisation degree is a number belonging to the [ -1 , + 1 ] interval . principally slope orientation oflen . elevation Dever Fuzzy neural network for ...
Page 1222
... degree is a degree of inclusion of m ( p ) in the upper approximation of m ( q ) obtained by " stretching " the set of interpretations @ satisfying q in a suitable way . The companion degree of consistency is defined by Cs ( q | p ) ...
... degree is a degree of inclusion of m ( p ) in the upper approximation of m ( q ) obtained by " stretching " the set of interpretations @ satisfying q in a suitable way . The companion degree of consistency is defined by Cs ( q | p ) ...
Page 1265
... degree : ( 0.16 , 0.60 ) overlaps Y_AXIS to a degree : ( 0.25 , 0.37 ) UPPER BOUND : 0.60 RIGHT BOUND : 0.38 extends out to LOWER SIDE to a degree : ( 0 , 0.76 ) extends out to LEFT SIDE to a degree : ( 0 , 0.78 ) Ob4 of type partition ...
... degree : ( 0.16 , 0.60 ) overlaps Y_AXIS to a degree : ( 0.25 , 0.37 ) UPPER BOUND : 0.60 RIGHT BOUND : 0.38 extends out to LOWER SIDE to a degree : ( 0 , 0.76 ) extends out to LEFT SIDE to a degree : ( 0 , 0.78 ) Ob4 of type partition ...
Contents
Hybrid Systems | 1069 |
Special Workshop on NeuroFuzzy Modeling Organized | 1070 |
Invited Lecture | 1071 |
Copyright | |
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a-level a-level sets analog antecedent applications approach architecture cell computed constraints corresponding defined defuzzification degree Dubois dynamic equations evaluation example expert networks Figure fuzzy control systems fuzzy controller fuzzy inference fuzzy logic fuzzy logic control fuzzy numbers fuzzy rules fuzzy sets Fuzzy Systems Genetic Algorithms Group IEEE IEEE Trans implemented input variables Is(q knowledge base layer learning algorithm linear matching maximum measures membership functions method minimization monotonic Neural Networks node number of rules object recognition objective function obtained operation optimal solution output parameters partition pattern performance pixel possibilistic possibilistic logic possibility distribution Prade problem Proc procedure processor proposed reference reflexive relation reinforcement learning represented respect RFALCON rough set rule base scheduling segments signal simulation sliding mode control space step string structure Sugeno t-norm task techniques tion tuning vector