Reducing bias and inefficiency in the selection algorithm
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Practical neural network recipes in C++
Practical neural network recipes in C++
Empirical study on learning in fuzzy systems by rice taste analysis
Fuzzy Sets and Systems
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
A simple but powerful heuristic method for generating fuzzy rules from numerical data
Fuzzy Sets and Systems
Neural Network Models: An Analysis
Neural Network Models: An Analysis
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Information Sciences: an International Journal - Recent advances in genetic fuzzy systems
Foundations of Neuro-Fuzzy Systems
Foundations of Neuro-Fuzzy Systems
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
International Journal of Intelligent Systems
A TSK type fuzzy rule based system for stock price prediction
Expert Systems with Applications: An International Journal
A filter model for feature subset selection based on genetic algorithm
Knowledge-Based Systems
Proceedings of the 2008 conference on Artificial Intelligence Research and Development: Proceedings of the 11th International Conference of the Catalan Association for Artificial Intelligence
Electric load forecasting using a fuzzy ART&ARTMAP neural network
Applied Soft Computing
Computational Intelligence: Collaboration, Fusion and Emergence
Computational Intelligence: Collaboration, Fusion and Emergence
Evolving neural network for printed circuit board sales forecasting
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Knowledge-Based Systems
Business Intelligence in Economic Forecasting: Technologies and Techniques
Business Intelligence in Economic Forecasting: Technologies and Techniques
Integration of genetic fuzzy systems and artificial neural networks for stock price forecasting
Knowledge-Based Systems
An intelligent ACO-SA approach for short term electricity load prediction
ICIC'10 Proceedings of the Advanced intelligent computing theories and applications, and 6th international conference on Intelligent computing
A case-based knowledge system for safety evaluation decision making of thermal power plants
Knowledge-Based Systems
Expert Systems with Applications: An International Journal
A knowledge-based system approach for a context-aware system
Knowledge-Based Systems
Methods for model-based reasoning within agent-based Ambient Intelligence applications
Knowledge-Based Systems
A decision support system for managing combinatorial problems in container terminals
Knowledge-Based Systems
Parameter control in evolutionary algorithms
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A proposal for improving the accuracy of linguistic modeling
IEEE Transactions on Fuzzy Systems
Self-learning fuzzy controllers based on temporal backpropagation
IEEE Transactions on Neural Networks
A collaborative fuzzy-neural approach for long-term load forecasting in Taiwan
Computers and Industrial Engineering
A pattern-based knowledge editing system for building clinical Decision Support Systems
Knowledge-Based Systems
Swarm intelligence approaches to estimate electricity energy demand in Turkey
Knowledge-Based Systems
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Knowledge-based expert systems are becoming one of the major tools for scientists and engineers nowadays, since they have many attractive features and can be called upon to deal with real/complex engineering application problems which are not easy to solve by orthodox methods. Meanwhile, increasing worldwide demand for different types of energy requires development of advanced intelligent forecasting tools to provide a basis from which decisions and plans can be made. This study presents a new approach called ''Cooperative Ant Colony Optimization-Genetic Algorithm'' (COR-ACO-GA), to construct expert systems with the ability to model and simulate fluctuations of energy demand under the influence of related factors. The proposed approach has two main stages, at the first stage it uses genetic algorithms to generate data base of the expert system, and at the second stage it adopts ant colony optimization to learn linguistic fuzzy rules such that degree of cooperation between data base and rule base increases and consequently performance of the algorithm improves. We evaluate capability of COR-ACO-GA by applying it on three case studies of annual electricity demand, natural gas demand and oil products demand in Iran. Results indicate that COR-ACO-GA provides more accurate-stable results than adaptive neuro-fuzzy inference systems (ANFISs) and artificial neural networks (ANNs), and can assist decision makers in making appropriate decisions and plans for a coming period.