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
Fuzzy engineering
Fuzzy cognitive maps: a model for intelligent supervisory control systems
Computers in Industry - ASI 1997
Qualitative optimization of Fuzzy Causal Rule Bases using Fuzzy Boolean Nets
Fuzzy Sets and Systems
Adaptive estimation of fuzzy cognitive maps with proven stability and parameter convergence
IEEE Transactions on Fuzzy Systems
Evolving fuzzy neural networks for supervised/unsupervised onlineknowledge-based learning
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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
Dynamical cognitive network - an extension of fuzzy cognitive map
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Quotient FCMs-a decomposition theory for fuzzy cognitive maps
IEEE Transactions on Fuzzy Systems
Dynamic domination in fuzzy causal networks
IEEE Transactions on Fuzzy Systems
Numerical and Linguistic Prediction of Time Series With the Use of Fuzzy Cognitive Maps
IEEE Transactions on Fuzzy Systems
A Self-Evolving Interval Type-2 Fuzzy Neural Network With Online Structure and Parameter Learning
IEEE Transactions on Fuzzy Systems
Review: Hybrid expert systems: A survey of current approaches and applications
Expert Systems with Applications: An International Journal
An EEG-based brain-computer interface for dual task driving detection
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part I
Bi-linear adaptive estimation of Fuzzy Cognitive Networks
Applied Soft Computing
An intelligent neuro fuzzy temporal knowledge representation model for mining temporal patterns
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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The fuzzy cognitive map (FCM) has gradually emerged as a powerful paradigm for knowledge representation and a simulation mechanism that is applicable to numerous research and application fields. However, since efficient methods to determine the states of the investigated system and to quantify causalities that are the very foundations of FCM theory are lacking, constructing FCMs for complex causal systems greatly depends on expert knowledge. The manually developed models have a substantial shortcoming due to the model subjectivity and difficulties with assessing its reliability. In this paper, we proposed a fuzzy neural network to enhance the learning ability of FCMs. Our approach incorporates the inference mechanism of conventional FCMs with the determination of membership functions, as well as the quantification of causalities. In this manner, FCM models of the investigated systems can automatically be constructed from data and, therefore, operate with less human intervention. In the employed fuzzy neural network, the concept of mutual subsethood is used to describe the causalities, which provides more transparent interpretation for causalities in FCMs. The effectiveness of the proposed approach in handling the prediction of time series is demonstrated through many numerical simulations.