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.
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© 2006 Springer-Verlag Berlin Heidelberg
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Xue, LH., Huang, HZ., Hu, J., Miao, Q., Ling, D. (2006). RAOGA-Based Fuzzy Neural Network Model of Design Evaluation. In: Huang, DS., Li, K., Irwin, G.W. (eds) Computational Intelligence. ICIC 2006. Lecture Notes in Computer Science(), vol 4114. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-37275-2_27
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DOI: https://doi.org/10.1007/978-3-540-37275-2_27
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37274-5
Online ISBN: 978-3-540-37275-2
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