Advertisement

RAOGA-Based Fuzzy Neural Network Model of Design Evaluation

  • Li-Hua Xue
  • Hong-Zhong Huang
  • Jun Hu
  • Qiang Miao
  • Dan Ling
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4114)

Abstract

This paper presents a new Fuzzy Neural Network (FNN) model to evaluate design alternatives in conceptual design. In the proposed method, a fuzzy reasoning based on feedforward neural network is used to evaluate concepts, and a learning algorithm based on ranking-based adaptive evolutionary operator genetic algorithm (RAOGA) is utilized to adjust fuzzy weights and thresholds with fuzzy inputs and outputs in FNN.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Huang, H.Z., Bo, R.F., Chen, W.: An Integrated Computational Intelligence Approach to Product Concept Generation and Evaluation. Mechanism and Machine Theory 41(5), 567–583 (2006)zbMATHCrossRefGoogle Scholar
  2. 2.
    Gu, Y.K., Huang, H.Z.: Fuzzy Mapping between Physical Domain and Function Domain in Design Process. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 12(1), 7–20 (2004)zbMATHCrossRefMathSciNetGoogle Scholar
  3. 3.
    Huang, H.Z., Zu, X.: Hierarchical Timed Colored Petri Nets Based Product Development Process Modeling. In: Shen, W.-m., Lin, Z., Barthès, J.-P.A., Li, T.-Q. (eds.) CSCWD 2004. LNCS, vol. 3168, pp. 378–387. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  4. 4.
    Thurston, D.L., Carnahan, J.V.: Fuzzy Ratings and Utility Analysis in Preliminary Design Evaluation of Multiple Attributes. ASME Journal of Mechanical Design 114, 648–658 (1992)CrossRefGoogle Scholar
  5. 5.
    Vanegas, L.V., Labib, A.W.: Application of New Fuzzy-Weighted Average (NFWA) Method to Engineering Design Evaluation. International Journal of Production Research 39, 1147–1162 (2001)zbMATHCrossRefGoogle Scholar
  6. 6.
    Ishibuchi, H., Kwon, K., Tanaka, H.: A Learning Algorithm of Fuzzy Neural Networks with Triangular Fuzzy Weights. Fuzzy Sets and Systems 71, 277–293 (1995)CrossRefGoogle Scholar
  7. 7.
    Kuo, R.J., Xue, K.C.: An Intelligent Sales Forecasting System through Integration of Artificial Neural Network and Fuzzy Neural Network. Computers in Industry 37, 1–15 (1998)CrossRefGoogle Scholar
  8. 8.
    Aliev, R.A., Fazlollahi, B., Vahidov, R.M.: Genetic Based Learning of Fuzzy Neural Networks. Part I: feed-forward fuzzy neural networks. Fuzzy Sets and Systems 118, 351–358 (2001)zbMATHMathSciNetGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Li-Hua Xue
    • 1
    • 2
  • Hong-Zhong Huang
    • 1
  • Jun Hu
    • 1
  • Qiang Miao
    • 1
  • Dan Ling
    • 1
  1. 1.School of Mechatronics Eng.University of Electronic Science and Technology of ChinaChengduChina
  2. 2.School of Mechanical Eng.Dalian University of TechnologyDalianChina

Personalised recommendations