Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Time Series Analysis, Forecasting and Control
Time Series Analysis, Forecasting and Control
Parameter Selection in Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
GA-PSO based vector control of indirect three phase induction motor
Applied Soft Computing
A novel hybrid algorithm for function approximation
Expert Systems with Applications: An International Journal
Forecasting Thailand's rice export: Statistical techniques vs. artificial neural networks
Computers and Industrial Engineering
A hybrid genetic algorithm and particle swarm optimization for multimodal functions
Applied Soft Computing
Hybridization of intelligent techniques and ARIMA models for time series prediction
Fuzzy Sets and Systems
Integration of particle swarm optimization and genetic algorithm for dynamic clustering
Information Sciences: an International Journal
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This paper proposes a hybrid evolutionary algorithm based radial basis function neural network (RBFnn) for sales forecasting. The proposed hybrid of particle swarm and genetic algorithm based optimization (HPSGO) algorithm gathers virtues of particle swarm optimization (PSO) and genetic algorithm (GA) to improve the learning performance of RBFnn. The diversity of chromosomes results in higher chance to search in the direction of global minimum instead of being confined to local minimum. Experimental results of papaya milk sales data show that the proposed HPSGO algorithm outperforms PSO, GA and Box-Jenkins model in accuracy.