On Fuzzy Reasoning Using Matrix Representation of Extended Fuzzy Petri Nets
Fundamenta Informaticae - Concurrency Specification and Programming (CS&P 2003)
A mobile physiological monitoring system for patient transport
Journal of High Speed Networks - Broadband Multimedia Sensor Networks in Healthcare Applications
Combining Concept Maps and Petri Nets to Generate Intelligent Tutoring Systems: A Possible Approach
MICAI '08 Proceedings of the 7th Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Discrete-event controller design using Petri nets and fuzzy logic - preliminary study
WSEAS Transactions on Systems and Control
Vulnerability assessment of aircraft guarantee system based on improved FPN
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
An embedded mobile ECG reasoning system for elderly patients
IEEE Transactions on Information Technology in Biomedicine - Special section on new and emerging technologies in bioinformatics and bioengineering
Fuzzy cognitive maps for modeling complex systems
MICAI'10 Proceedings of the 9th Mexican international conference on Advances in artificial intelligence: Part I
A fuzzy cognitive maps modeling, learning and simulation framework for studying complex system
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation: new challenges on bioinspired applications - Volume Part II
An intelligent petri nets model based on competitive neural network
CSCWD'04 Proceedings of the 8th international conference on Computer Supported Cooperative Work in Design I
On Fuzzy Reasoning Using Matrix Representation of Extended Fuzzy Petri Nets
Fundamenta Informaticae - Concurrency Specification and Programming (CS&P 2003)
Hi-index | 0.00 |
Since knowledge in an expert system is vague and modified frequently, expert systems are fuzzy and dynamic. It is very important to design a dynamic knowledge inference framework which is adjustable according to knowledge variation as human cognition and thinking. A generalized fuzzy Petri net model, called adaptive fuzzy Petri net (AFPN), is proposed with this object in mind. AFPN not only has the descriptive advantages of the fuzzy Petri net, it also has learning ability like a neural network. Just as other fuzzy Petri net (FPN) models, AFPN can be used for knowledge representation and reasoning, but AFPN has one important advantage: it is suitable for dynamic knowledge, i.e., the weights of AFPN are adjustable. Based on the AFPN transition firing rule, a modified backpropagation learning algorithm is developed to assure the convergence of the weights