Structure identification of fuzzy model
Fuzzy Sets and Systems
Using genetic search to exploit the emergent behavior of neural networks
CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural computing: an introduction
Neural computing: an introduction
Fuzzy systems theory and its applications
Fuzzy systems theory and its applications
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Expert systems in business and finance: issues and applications
Expert systems in business and finance: issues and applications
Fuzzy Systems as Universal Approximators
IEEE Transactions on Computers
On the overtraining phenomenon of backpropagation neural networks
Mathematics and Computers in Simulation - Special issue on neural networks/neural computing
A flexible neurofuzzy cell structure for general fuzzy inference
Mathematics and Computers in Simulation - Special issue: Robotics
Efficient methods for fuzzy rule extraction from numerical data
Fuzzy logic and neural network handbook
Additive fuzzy systems: from function approximation to learning
Fuzzy logic and neural network handbook
A real-time expert data filtering system for industrial plant environments
ERIS '94 Proceedings of the European conference on Robotics and intelligent systems
Real-valued genetic algorithms for fuzzy grey prediction system
Fuzzy Sets and Systems
Efficient search for fuzzy models using genetic algorithm
Information Sciences—Informatics and Computer Science: An International Journal - Special issue on modeling with soft-computing
Redundant fuzzy rules exclusion by genetic algorithms
Fuzzy Sets and Systems
A genetic algorithm for optimizing Takagi-Sugeno fuzzy rule bases
Fuzzy Sets and Systems
Mathematics and Computers in Simulation - Special issue from the IMACS/IFAC international symposium on soft computing methods and applications: “SOFTCOM '99” (held in Athens, Greece)
A hybrid fuzzy modeling method for short-term load forecasting
Mathematics and Computers in Simulation - Special issue from the IMACS/IFAC international symposium on soft computing methods and applications: “SOFTCOM '99” (held in Athens, Greece)
Neural fuzzy relational systems with a new learning algorithm
Mathematics and Computers in Simulation - Special issue from the IMACS/IFAC international symposium on soft computing methods and applications: “SOFTCOM '99” (held in Athens, Greece)
Hybrid Neural Network and Expert Systems
Hybrid Neural Network and Expert Systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Knowledge-Based System Diagnosis, Supervision, and Control
Knowledge-Based System Diagnosis, Supervision, and Control
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Computational Intelligence Applications to Power Systems
Computational Intelligence Applications to Power Systems
Fuzzy Reasoning in Information, Decision, and Control Systems
Fuzzy Reasoning in Information, Decision, and Control Systems
Industrial Applications of Fuzzy Technology
Industrial Applications of Fuzzy Technology
An Introduction to Fuzzy Logic Applications in Intelligent Systems
An Introduction to Fuzzy Logic Applications in Intelligent Systems
Time Series Analysis, Forecasting and Control
Time Series Analysis, Forecasting and Control
A Genetic Approach for Simultaneous Design of Membership Functions and Fuzzy Control Rules
Journal of Intelligent and Robotic Systems
A Hierarchical Self-Organizing Map Model in Short-Term Load Forecasting
Journal of Intelligent and Robotic Systems
Neurofuzzy approaches to anticipation: a new paradigm forintelligent systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fuzzy relation equations and fuzzy inference systems: an insideapproach
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
ANNSTLF-a neural-network-based electric load forecasting system
IEEE Transactions on Neural Networks
Journal of Intelligent and Robotic Systems
ISTASC'05 Proceedings of the 5th WSEAS/IASME International Conference on Systems Theory and Scientific Computation
ICC'05 Proceedings of the 9th International Conference on Circuits
Multilayer neuro-fuzzy network for short term electric load forecasting
CSR'08 Proceedings of the 3rd international conference on Computer science: theory and applications
Power system short-term load forecasting based on PSO clustering analysis and Elman neural network
SMO'05 Proceedings of the 5th WSEAS international conference on Simulation, modelling and optimization
Short-term load forecasting using PSO-based phase space neural networks
SMO'05 Proceedings of the 5th WSEAS international conference on Simulation, modelling and optimization
Fuzzy neural very-short-term load forecasting based on chaotic dynamics reconstruction
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part III
Load forecasting using a multivariate meta-learning system
Expert Systems with Applications: An International Journal
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Electric load forecasting has received an increasing attention over the years by academic and industrial researchers and practitioners due to its major role for the effective and economic operation of power utilities. The aim of this paper is to provide a collective unified survey study on the application of computational intelligence (CI) model-free techniques to the short-term load forecasting of electric power plants. All four classes of CI methodologies, namely neural networks (NNs), fuzzy logic (FL), genetic algorithms (GAs) and chaos are addressed. The paper starts with some background material on model-based and knowledge-based forecasting methodologies revealing a number of key issues. Then, the pure NN-based and FL-based forecasting methodologies are presented in some detail. Next, the hybrid neurofuzzy forecasting methodology (ANFIS, GARIC and Fuzzy ART variations), and three other hybrid CI methodologies (KB-NN, Chaos-FL, Neurofuzzy-GA) are reviewed. The paper ends with eight representative case studies, which show the relative merits and performance that can be achieved by the various forecasting methodologies under a large repertory of geographic, weather and other peculiar conditions. An overall evaluation of the state-of-art of the field is provided in the conclusions.