doi: 10.4304/jsw.6.10.2050-2055
Optimizing for Large Time Delay Systems by BP Neural Network and Evolutionary Algorithm Improving
- 1 Fujian Key Laboratory of the Brain-Like Intelligent Systems, Xiamen University, Xiamen, China
- 2 Cognitive science department, Xiamen University, Xiamen, China
- 3 School of software, Xiamen University, Xiamen, China
- 4 Department of Computer Science, Xiamen University, Xiamen, China
Abstract
BP artificial neural network is a non-feedback network. This paper utilizes the initial weights of neural network to choose controller performance. Simultaneously according to the characteristics that process of central air-conditioning energy saving control is the system of multi-parameter and nonlinear time-varying complexity, we analysis and study its algorithm and system architecture. The experimental results demonstrate that new control system gets better results and energy saving.
Keywords
- Steady-state
- error;
- Robusfitness;
- BP
- Art
How to Cite
Fan Lin, Wenhua Zeng, Jianbing Xiahou, and Yi Jiang, "Optimizing for Large Time Delay Systems by BP Neural Network and Evolutionary Algorithm Improving," Journal of Software, vol. 6, no. 10, pp. 2050-2055, 2011. https://doi.org/ 10.4304/jsw.6.10.2050-2055
Copyright & License
Copyright © 2011 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).