Volume 6 Number 10 (Oct. 2011)
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JSW 2011 Vol.6(10): 2050-2055 ISSN: 1796-217X
doi: 10.4304/jsw.6.10.2050-2055

Optimizing for Large Time Delay Systems by BP Neural Network and Evolutionary Algorithm Improving

Fan Lin1, 2, 3, Wenhua Zeng3, Jianbing Xiahou3, Yi Jiang4
1Fujian Key Laboratory of the Brain-Like Intelligent Systems, Xiamen University, Xiamen, China
2Cognitive science department, Xiamen University, Xiamen, China
3School of software, Xiamen University, Xiamen, China
4Department 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.

Index Terms—Steady-state error; Robusfitness; BP Artificial Neural Network; Evolutionary Algorithm; Fuzzy PID Control Strategy

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Cite: Fan Lin, Wenhua Zeng, Jianbing Xiahou, 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.

General Information

ISSN: 1796-217X (Online)
Frequency:  Quarterly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKIGoogle Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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