Journal of Beijing University of Posts and Telecommunications

  • EI核心期刊

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2014, Vol. 37 ›› Issue (4): 39-43.doi: 10.13190/j.jbupt.2014.04.009

• Papers • Previous Articles     Next Articles

Garment Sales Forecast Method Based on Genetic Algorithm and BP Neural Network

LUO Rong-lei1,2, LIU Shao-hua3, SU Chen2   

  1. 1. School of Fashion, Zhejiang Sci-Tech University, Hangzhou 310018, China;
    2. Engineering Research Center of Clothing of Zhejiang Province, Hangzhou 310018, China;
    3. School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • Received:2013-07-07 Online:2014-08-28 Published:2014-08-09

Abstract:

The neural network learning models was proposed, focusing on complexity and particularity of product sales in garment industry. The network model was established to predict the impact on garment sales on basis of factor analysis and optimized by using genetic algorithms for each connection weights of back propagation (BP) neural network. The method combines the strong learning ability of the BP neural and the global search capability of genetic algorithms.

Key words: sales forecast, genetic algorithm, BP neural network

CLC Number: