International Journal of Man-Machine Studies
Graph Theory, 1736-1936
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Introduction to artificial neural systems
Introduction to artificial neural systems
Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary computation: toward a new philosophy of machine intelligence
Using fuzzy cognitive maps as a system model for failure modes and effects analysis
Information Sciences: an International Journal
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
An introduction to differential evolution
New ideas in optimization
Hybrid Evolutionary Search Method Based on Clusters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fundamentals of Artificial Neural Networks
Fundamentals of Artificial Neural Networks
Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
Numerical Optimization of Computer Models
Numerical Optimization of Computer Models
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Handbook of Evolutionary Computation
Handbook of Evolutionary Computation
Evolving the Topology and the Weights of Neural Networks Using a Dual Representation
Applied Intelligence
Journal of Global Optimization
Adaptive Random Fuzzy Cognitive Maps
IBERAMIA 2002 Proceedings of the 8th Ibero-American Conference on AI: Advances in Artificial Intelligence
Tracking Extrema in Dynamic Environments
EP '97 Proceedings of the 6th International Conference on Evolutionary Programming VI
Fuzzy Cognitive Maps in modeling supervisory control systems
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
An overview of evolutionary algorithms for parameter optimization
Evolutionary Computation
Modeling complex systems using fuzzy cognitive maps
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Contextual fuzzy cognitive map for decision support in geographic information systems
IEEE Transactions on Fuzzy Systems
On causal inference in fuzzy cognitive maps
IEEE Transactions on Fuzzy Systems
Fuzzy trust evaluation and credibility development in multi-agent systems
Applied Soft Computing
Fuzzy cognitive map learning based on multi-objectiveparticle swarm optimization
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Brain tumor characterization using the soft computing technique of fuzzy cognitive maps
Applied Soft Computing
Expert Systems with Applications: An International Journal
A fuzzy cognitive map approach for effect-based operations: An illustrative case
Information Sciences: an International Journal
Benchmarking main activation functions in fuzzy cognitive maps
Expert Systems with Applications: An International Journal
Application of fuzzy cognitive maps for cotton yield management in precision farming
Expert Systems with Applications: An International Journal
IEEE Transactions on Information Technology in Biomedicine - Special section on computational intelligence in medical systems
Expert Systems with Applications: An International Journal
Structural damage detection using fuzzy cognitive maps and Hebbian learning
Applied Soft Computing
Training Fuzzy Cognitive Maps via Extended Great Deluge Algorithm with applications
Computers in Industry
Ranking fuzzy cognitive map based scenarios with TOPSIS
Expert Systems with Applications: An International Journal
Learning Fuzzy Grey Cognitive Maps using Nonlinear Hebbian-based approach
International Journal of Approximate Reasoning
A Fuzzy Grey Cognitive Maps-based Decision Support System for radiotherapy treatment planning
Knowledge-Based Systems
Towards Hebbian learning of Fuzzy Cognitive Maps in pattern classification problems
Expert Systems with Applications: An International Journal
An expert fuzzy cognitive map for reactive navigation of mobile robots
Fuzzy Sets and Systems
Fuzzy cognitive maps for artificial emotions forecasting
Applied Soft Computing
A fuzzy cognitive map of the psychosocial determinants of obesity
Applied Soft Computing
Yield prediction in apples using Fuzzy Cognitive Map learning approach
Computers and Electronics in Agriculture
Stock index tracking by Pareto efficient genetic algorithm
Applied Soft Computing
Linear and sigmoidal fuzzy cognitive maps: An analysis of fixed points
Applied Soft Computing
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A novel hybrid method based on evolutionary computation techniques is presented in this paper for training Fuzzy Cognitive Maps. Fuzzy Cognitive Maps is a soft computing technique for modeling complex systems, which combines the synergistic theories of neural networks and fuzzy logic. The methodology of developing Fuzzy Cognitive Maps relies on human expert experience and knowledge, but still exhibits weaknesses in utilization of learning methods and algorithmic background. For this purpose, we investigate a coupling of differential evolution algorithm and unsupervised Hebbian learning algorithm, using both the global search capabilities of Evolutionary strategies and the effectiveness of the nonlinear Hebbian learning rule. The use of differential evolution algorithm is related to the concept of evolution of a number of individuals from generation to generation and that of nonlinear Hebbian rule to the concept of adaptation to the environment by learning. The hybrid algorithm is introduced, presented and applied successfully in real-world problems, from chemical industry and medicine. Experimental results suggest that the hybrid strategy is capable to train FCM effectively leading the system to desired states and determining an appropriate weight matrix for each specific problem.