International Journal of Man-Machine Studies
Hidden patterns in combined and adaptive knowledge networks
International Journal of Approximate Reasoning
Signal flow graphs vs fuzzy cognitive maps in application to qualitative circuit analysis
International Journal of Man-Machine Studies
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Fuzzy engineering
Automatic construction of FCMs
Fuzzy Sets and Systems
Tackling Real-Coded Genetic Algorithms: Operators and Tools for Behavioural Analysis
Artificial Intelligence Review
Fuzzy cognitive maps: a model for intelligent supervisory control systems
Computers in Industry - ASI 1997
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Adaptive Random Fuzzy Cognitive Maps
IBERAMIA 2002 Proceedings of the 8th Ibero-American Conference on AI: Advances in Artificial Intelligence
Fuzzy Cognitive Maps Learning Using Particle Swarm Optimization
Journal of Intelligent Information Systems
Fuzzy Cognitive Maps in modeling supervisory control systems
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Predictive models for the breeder genetic algorithm i. continuous parameter optimization
Evolutionary Computation
Modeling complex systems using fuzzy cognitive maps
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A fuzzy cognitive map approach to differential diagnosis of specific language impairment
Artificial Intelligence in Medicine
Unsupervised learning techniques for fine-tuning fuzzy cognitive map causal links
International Journal of Human-Computer Studies
Comparing the inference capabilities of binary, trivalent and sigmoid fuzzy cognitive maps
Information Sciences: an International Journal
Application of Fuzzy Cognitive Maps for Stock Market Modeling and Forecasting
IEA/AIE '08 Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence
A Prolog Based System That Assists Experts to Construct and Simulate Fuzzy Cognitive Maps
SETN '08 Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications
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
Designing fuzzy-genetic learner model based on multi-agent systems in supply chain management
Expert Systems with Applications: An International Journal
International Journal of Data Analysis Techniques and Strategies
Adaptive estimation of fuzzy cognitive maps with proven stability and parameter convergence
IEEE Transactions on Fuzzy Systems
Mining temporal medical data using adaptive fuzzy cognitive maps
HSI'09 Proceedings of the 2nd conference on Human System Interactions
Fuzzy integrated vulnerability assessment model for critical facilities in combating the terrorism
Expert Systems with Applications: An International Journal
Using fuzzy cognitive map for evaluation of RFID-based reverse logistics services
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Transformation of cognitive maps
IEEE Transactions on Fuzzy Systems
A trust-based model using learning FCM for partner selection in the virtual enterprises
ICIC'07 Proceedings of the intelligent computing 3rd international conference on Advanced intelligent computing theories and applications
Expert Systems with Applications: An International Journal
Genetic algorithm dynamic performance evaluation for RFID reverse logistic management
Expert Systems with Applications: An International Journal
A divide and conquer method for learning large Fuzzy Cognitive Maps
Fuzzy Sets and Systems
Expert Systems with Applications: An International Journal
Training Fuzzy Cognitive Maps via Extended Great Deluge Algorithm with applications
Computers in Industry
Optimization and adaptation of dynamic models of fuzzy relational cognitive maps
RSFDGrC'11 Proceedings of the 13th international conference on Rough sets, fuzzy sets, data mining and granular computing
MICAI'11 Proceedings of the 10th international conference on Artificial Intelligence: advances in Soft Computing - Volume Part II
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
Learning fuzzy cognitive maps from data by ant colony optimization
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Bagged nonlinear hebbian learning algorithm for fuzzy cognitive maps working on classification tasks
SETN'12 Proceedings of the 7th Hellenic conference on Artificial Intelligence: theories and applications
A fuzzy cognitive map of the psychosocial determinants of obesity
Applied Soft Computing
Bi-linear adaptive estimation of Fuzzy Cognitive Networks
Applied Soft Computing
Different dynamic causal relationship approaches for cognitive maps
Applied Soft Computing
RuleML representation and simulation of Fuzzy Cognitive Maps
Expert Systems with Applications: An International Journal
Yield prediction in apples using Fuzzy Cognitive Map learning approach
Computers and Electronics in Agriculture
Dynamic risks modelling in ERP maintenance projects with FCM
Information Sciences: an International Journal
Fuzzy cognitive network: A general framework
Intelligent Decision Technologies
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Fuzzy cognitive maps (FCMs) are a very convenient, simple, and powerful tool for simulation and analysis of dynamic systems. They were originally developed in 1980 by Kosko, and since then successfully applied to numerous domains, such as engineering, medicine, control, and political affairs. Their popularity stems from simplicity and transparency of the underlying model. At the same time FCMs are hindered by necessity of involving domain experts to develop the model. Since human experts are subjective and can handle only relatively simple networks (maps), there is an urgent need to develop methods for automated generation of FCM models. This study proposes a novel learning method that is able to generate FCM models from input historical data, and without human intervention. The proposed method is based on genetic algorithms, and requires only a single state vector sequence as an input. The paper proposes and experimentally compares several different design alternatives of genetic optimization and thoroughly tests and discusses the best design. Extensive benchmarking tests, which involve 200 FCMs with varying size and density of connections, performed on both synthetic and real-life data quantifies the performance of the development method and emphasizes its suitability.