Title :
Optimal prediction model using improved differential evolution algorithm
Author :
Zheng, Ming-Chang ; Chou, Jyh-Horng ; Chen, Shinn-Horng
Author_Institution :
Inst. of Eng. Sci. & Technol., Nat. Kaohsiung First Univ. of Sci. & Technol., Kaohsiung, Taiwan
Abstract :
A Taguchi-based the differential evolution (TDE) is applied as an improved the differential evolution to solve the global optimization. The differential evolution (DE) is an easy and valid evolutionary algorithm for fitness function optimization. For grey forecasting model (GM) which is a time series forecasting model, the parameters are calculated by the TDE. The academic research of Wang and Hsu is a base of this paper. Finally, the forecasted result of TDEGM is superior to other evolutionary algorithms.
Keywords :
differential equations; evolutionary computation; forecasting theory; optimisation; time series; Taguchi-based differential evolution; academic research; evolutionary algorithm; fitness function optimization; global optimization; grey forecasting model; improved differential evolution algorithm; optimal prediction model; time series forecasting model; Cybernetics; Forecasting; Genetic algorithms; Integrated circuit modeling; Machine learning; Mathematical model; Predictive models; Evolution algorithm; Grey forecasting model; Optimal;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2011 International Conference on
Conference_Location :
Guilin
Print_ISBN :
978-1-4577-0305-8
DOI :
10.1109/ICMLC.2011.6016882
