A fuzzy Petri net for knowledge representation and reasoning
Information Processing Letters
Knowledge Representation in Fuzzy Logic
IEEE Transactions on Knowledge and Data Engineering
Uncertainty Management in Expert Systems Using Fuzzy Petri Nets
IEEE Transactions on Knowledge and Data Engineering
A High-Level Petri Net for Goal-Directed Semantics of Horn Clause Logic
IEEE Transactions on Knowledge and Data Engineering
Knowledge Validation: Principles and Practice
IEEE Expert: Intelligent Systems and Their Applications
UVT: A Unification-Based Tool for Knowledge Base Verification
IEEE Expert: Intelligent Systems and Their Applications
Mathematics and Computers in Simulation
A hybrid genetic algorithm and particle swarm optimization for multimodal functions
Applied Soft Computing
Nonlinear inertia weight variation for dynamic adaptation in particle swarm optimization
Computers and Operations Research
An improved GA and a novel PSO-GA-based hybrid algorithm
Information Processing Letters
Improving fuzzy knowledge integration with particle swarmoptimization
Expert Systems with Applications: An International Journal
The fully informed particle swarm: simpler, maybe better
IEEE Transactions on Evolutionary Computation
A generalized fuzzy Petri net model
IEEE Transactions on Fuzzy Systems
Hi-index | 12.05 |
Information in some fields like complex product design is usually imprecise, vague and fuzzy. Therefore, it would be very useful to design knowledge representation model capable to be adjusted according to information dynamics. Aiming at this objective, a knowledge representation scheme is proposed, which is called DRFK (Dynamic Representation of Fuzzy Knowledge). This model has both the features of a fuzzy Petri net and the learning ability of evolutionary algorithms. An efficient Genetic Particle Swarm Optimization (GPSO) learning algorithm is developed to solving fuzzy knowledge representation parameters. Being trained, a DRFK model can be used for dynamic knowledge representation and inference. Finally, an example is included as an illustration.