Abstract
This paper presents a method of collaborative design optimization based on knowledge discovery. Firstly, a knowledge discovery approach based on simulation data is presented. Rules are extracted by knowledge discovery algorithm, and each rule is divided into several intervals. Secondly, a collaborative optimization model is established. In the model, the consistency intervals are derived from intervals of knowledge discovery. The model is resolved by genetic arithmetic. Finally, The method is demonstrated by a parameter design problem of piston-connecting mechanism of automotive engine. The proposed method can improve the robustness of collaborative design optimization.
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Hu, J., Peng, Y. (2006). Collaborative Design Optimization Based on Knowledge Discovery from Simulation. In: Gelbukh, A., Reyes-Garcia, C.A. (eds) MICAI 2006: Advances in Artificial Intelligence. MICAI 2006. Lecture Notes in Computer Science(), vol 4293. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11925231_63
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DOI: https://doi.org/10.1007/11925231_63
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-49026-5
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