Title :
Metal Model Based Fuzzy Petri Nets Back Propagation Learning Algorithm
Author :
Tang, Xin Min ; Zhong, Shi Sheng
Author_Institution :
Harbin Inst. of Technol., Harbin
Abstract :
In fuzzy production rule-based system, fuzzy Petri nets (FPN) is widely used for its advantage of fuzzy knowledge representation and concurrent reasoning. For the reason that back propagation (BP) algorithm can not be applied to learning of FPN directly without add virtual nodes. To overcome the drawback, a metal fuzzy Petri nets (MFPN) model is proposed. FPN mapped from four elementary production rules can be uniformed by MFPN. A continuous function maps from certainty factor of antecedent propositions to that of consequent ones in MFPN is defined, based on which, a forward continues reasoning algorithm is presented, then the gradient function of certainty factor of consequent propositions with respect to input arc weight is given. To improve convergence speed, Levenberg-Marquardt method is adopted to arc weight optimization.
Keywords :
Petri nets; backpropagation; fuzzy reasoning; fuzzy set theory; gradient methods; knowledge based systems; knowledge representation; arc weight optimization; backpropagation learning algorithm; certainty factor; concurrent reasoning; continuous function maps; fuzzy knowledge representation; fuzzy production rule-based system; gradient function; metal fuzzy Petri nets; Artificial neural networks; Convergence; Fuzzy logic; Fuzzy reasoning; Fuzzy systems; Knowledge representation; Optimization methods; Petri nets; Production systems; Systems engineering and theory; Levenberg-Marquardt algorithm; back propagation algorithm; fuzzy Petri nets;
Conference_Titel :
Computational Engineering in Systems Applications, IMACS Multiconference on
Conference_Location :
Beijing
Print_ISBN :
7-302-13922-9
Electronic_ISBN :
7-900718-14-1
DOI :
10.1109/CESA.2006.4281940
