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New Technology of Library and Information Service  2012, Vol. 28 Issue (1): 63-67    DOI: 10.11925/infotech.1003-3513.2012.01.11
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Application Research of Improved Genetic Neural Network Algorithm in Sales Forecast
Tai Lijun1, Hu Rufu1, Zhao Han2, Chen Caowei1
1. School of Mechanical Engineering, Ningbo University of Technology, Ningbo 315000, China;
2. School of Mechanical and Automotive Engineering, Hefei University of Technology, Hefei 230009, China
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Abstract  According to the insufficiency existed in traditional BP algorithm for sales forecast such as low learn rate,low convergence and falling into local optimization, etc,the improvement measures are proposed. The effectiveness and the convergence of the algorithm are improved by self-adapted learning rate, the adaptability is improved by the additive momentum, and the weight of neural network is optimized by modified genetic algorithm. The large-scale search optimum ability of modified genetic algorithm is used to implement the purpose of fast search optimum and accurate prediction. Finally, an example verifies this algorithm.
Key wordsBP algorithm      Genetic algorithm      Sales forecast     
Received: 12 October 2011      Published: 26 February 2012



Cite this article:

Tai Lijun, Hu Rufu, Zhao Han, Chen Caowei. Application Research of Improved Genetic Neural Network Algorithm in Sales Forecast. New Technology of Library and Information Service, 2012, 28(1): 63-67.

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