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

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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.