• DocumentCode
    532508
  • Title

    Improving central air conditioning energy saving control system through BP neural network and genetic algorithm

  • Author

    Zengdong, Zhang ; Ziwei, Ni ; Yi, Jiang ; Fan, Lin

  • Author_Institution
    Coll. of Inf. Sci. & Technol., Xiamen Univ., Xiamen, China
  • Volume
    1
  • fYear
    2010
  • fDate
    22-24 Oct. 2010
  • 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
    air conditioning; backpropagation; genetic algorithms; neurocontrollers; nonlinear control systems; power control; time-varying systems; BP neural network; backpropagation; central air conditioning; energy saving control system; genetic algorithm; multi-parameter complexity; nonlinear time-varying complexity; Cooling; Optimization; Process control; Reliability engineering; BP Artificial Neural Network; Fuzzy PID Control Strategy; Genetic Algorithm; Robustness; Steady-state error;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Application and System Modeling (ICCASM), 2010 International Conference on
  • Conference_Location
    Taiyuan
  • Print_ISBN
    978-1-4244-7235-2
  • Electronic_ISBN
    978-1-4244-7237-6
  • Type

    conf

  • DOI
    10.1109/ICCASM.2010.5620656
  • Filename
    5620656