Evolutive Identification of Fuzzy Systems for Time-Series Prediction
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Evolved RBF Networks for Time-Series Forecasting and Function Approximation
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
New Methodology for Structure Identification of Fuzzy Controllers in Real Time
IBERAMIA 2002 Proceedings of the 8th Ibero-American Conference on AI: Advances in Artificial Intelligence
Evolutionary Training of Neuro-fuzzy Patches for Function Approximation
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
A Novel Approach to Self-Adaptation of Neuro-fuzzy Controllers in Real Time
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Connectionist Models of Neurons, Learning Processes and Artificial Intelligence-Part I
RBF Neural Networks, Multiobjective Optimization and Time Series Forecasting
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Connectionist Models of Neurons, Learning Processes and Artificial Intelligence-Part I
Expert Mutation Operators for the Evolution of Radial Basis Function Neural Networks
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Connectionist Models of Neurons, Learning Processes and Artificial Intelligence-Part I
EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
International Journal of Approximate Reasoning
Evolving structure and parameters of fuzzy models with interpretable membership functions
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Automatic tuning of complex fuzzy systems with Xfuzzy
Fuzzy Sets and Systems
Hybridization of intelligent techniques and ARIMA models for time series prediction
Fuzzy Sets and Systems
Data-driven fuzzy clustering based on maximum entropy principle and PSO
Expert Systems with Applications: An International Journal
TaSe, a Taylor series-based fuzzy system model that combines interpretability and accuracy
Fuzzy Sets and Systems
Perspectives of fuzzy systems and control
Fuzzy Sets and Systems
Studying the capacity of grammatical encoding to generate FNN architectures
IWANN'03 Proceedings of the Artificial and natural neural networks 7th international conference on Computational methods in neural modeling - Volume 1
Auto-adaptive neural network tree structure based on complexity estimator
IWANN'03 Proceedings of the Artificial and natural neural networks 7th international conference on Computational methods in neural modeling - Volume 1
Local-global neuro-fuzzy system for color change modelling
International Journal of Hybrid Intelligent Systems - Advances in Intelligent Agent Systems
A GMDH-based fuzzy modeling approach for constructing TS model
Fuzzy Sets and Systems
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part I
Analysis of the TaSe-II TSK-Type fuzzy system for function approximation
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
New technique for initialization of centres in TSK clustering-based fuzzy systems
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
IWINAC'05 Proceedings of the First international work-conference on the Interplay Between Natural and Artificial Computation conference on Artificial Intelligence and Knowledge Engineering Applications: a bioinspired approach - Volume Part II
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
Approximating i/o data using radial basis functions: a new clustering-based approach
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
Clustering-Based TSK neuro-fuzzy model for function approximation with interpretable sub-models
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
TaSe model for long term time series forecasting
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
A global-local optimization approach to parameter estimation of RBF-type models
Information Sciences: an International Journal
New Online Self-Evolving Neuro Fuzzy controller based on the TaSe-NF model
Information Sciences: an International Journal
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In this paper, a systematic design is proposed to determine fuzzy system structure and learning its parameters, from a set of given training examples. In particular, two fundamental problems concerning fuzzy system modeling are addressed: 1) fuzzy rule parameter optimization and 2) the identification of system structure (i.e., the number of membership functions and fuzzy rules). A four-step approach to build a fuzzy system automatically is presented: Step 1 directly obtains the optimum fuzzy rules for a given membership function configuration. Step 2 optimizes the allocation of the membership functions and the conclusion of the rules, in order to achieve a better approximation. Step 3 determines a new and more suitable topology with the information derived from the approximation error distribution; it decides which variables should increase the number of membership functions. Finally, Step 4 determines which structure should be selected to approximate the function, from the possible configurations provided by the algorithm in the three previous steps. The results of applying this method to the problem of function approximation are presented and then compared with other methodologies proposed in the bibliography