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 Predicting Product Variant Design Time Based on PSO Algorithm

  

  1. 1. School of Management, Northwestern Polytechnical University, Xi’an 710072, China;

     2. School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China
  • Received:2015-05-15 Online:2015-09-21 Published:2015-09-24

Abstract:  Before product secondary development, it is very difficult to forecast product variant design time. A variant design time prediction method based on the combination of the extremum disturbed particle swarm optimization (tPSO) with fuzzy neural network (FNN) is proposed. First of all, the time factor set is designated and the corresponding FNN time prediction model is established. However, the typical algorithm of FNN is easy to fall into local minimum, slow convergence speed and low learning efficiency. And then, the FNN model is optimized by tPSO to overcome disadvantages above. At last, the method is verified by the time prediction of printer variant design. The result indicates that the model is feasible and effective.

Key words:  product variant design, design time prediction, particle swarm optimization, fuzzy neural network