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Fast Modeling Methods for Complex System with Separable Features
Chen C(陈辰); Luo ZT(罗长童); Jiang ZL(姜宗林)
会议录名称2017 10TH INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN (ISCID), VOL. 1
2017
会议名称10th International Symposium on Computational Intelligence and Design (ISCID)
会议日期DEC 09-10, 2017
会议地点Hangzhou, PEOPLES R CHINA
摘要

Data-driven modeling plays an increasingly important role in different areas of engineering. For most of existing methods, such as genetic programming (GP), the convergence speed might be too slow for large scale problems with a large number of variables. Fortunately, in many applications, the target models are separable in some sense. In this paper, we analyze different types of separability and establish a generalized separable model (GSM). In order to get the structure of the GSM, a multi-level block search method is proposed, in which the target model is decomposed into a number of blocks, further into minimal blocks and factors. Compare to the conventional GP, the new method can make large reductions to the search space. The minimal blocks and factors are optimized and assembled with a global optimization search engine, low dimensional simplex evolution (LDSE). An extensive study between the proposed method and a state-of-the-art data-driven fitting tool, Eureqa, has been presented with several man-made problems. Test results indicate that the proposed method is more effective and efficient under all the investigated cases.

关键词Data-driven Modeling Genetic Programming Generalized Separable Model Multi-level Block Search
WOS记录号WOS:000427991100045
资助信息This work was supported by the National Natural Science Foundation of China (Grant No. 11532014).
ISBN号978-1-5386-3675-6
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收录类别EI
语种英语
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被引频次:1[WOS]   [WOS记录]     [WOS相关记录]
文献类型会议论文
条目标识符http://dspace.imech.ac.cn/handle/311007/75552
专题高温气体动力学国家重点实验室
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GB/T 7714
Chen C,Luo ZT,Jiang ZL. Fast Modeling Methods for Complex System with Separable Features[C],2017.
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