Neural-Network-Driven Fuzzy Optimum Selection for Mechanism Schemes

  • Authors:
  • Yingkui Gu;Xuewen He

  • Affiliations:
  • School of Mechanical & Electronical Engineering, Jiangxi University of Science and Technology, Ganzhou, Jiangxi 341000, China;School of Mechanical & Electronical Engineering, Jiangxi University of Science and Technology, Ganzhou, Jiangxi 341000, China

  • Venue:
  • ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
  • Year:
  • 2007

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Abstract

Product conceptual design is an innovative activity that is to form and optimize the projects of products. Identification of the best conceptual design candidate is a crucial step as design information is not complete and design knowledge is minimal at conceptual design stage. It is necessary to select the best scheme from feasible alternatives through comparison and filter. In this paper, the evaluation system of mechanism scheme is established firstly based on the performance analysis of the mechanism system and the opinions of experts. Then, the fuzzy optimum selection model of mechanism scheme evaluation is provided. Combined with the fuzzy optimum selection model with the neural network theory, a rational pattern of determining the topologic structure of network is provided. It also provides a weight-adjusted BP model of the neural network with the fuzzy optimum selection model for mechanism scheme. Finally, an example is given to verify the effective feasibility of the proposed method.