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Block building programming for symbolic regression
Chen C(陈辰); Luo ZT(罗长童); Jiang ZL(姜宗林)
2018-01-31
发表期刊NEUROCOMPUTING
卷号275页码:1973-1980
ISSN0925-2312
摘要

Symbolic regression that aims to detect underlying data-driven models has become increasingly important for industrial data analysis. For most existing algorithms such as genetic programming (GP), the convergence speed might be too slow for large-scale problems with a large number of variables. This situation may become even worse with increasing problem size. The aforementioned difficulty makes symbolic regression limited in practical applications. Fortunately, in many engineering problems, the independent variables in target models are separable or partially separable. This feature inspires us to develop a new approach, block building programming (BBP). BBP divides the original target function into several blocks, and further into factors. The factors are then modeled by an optimization engine (e.g. GP). Under such circumstances, BBP can make large reductions to the search space. The partition of separability is based on a special method, block and factor detection. Two different optimization engines are applied to test the performance of BBP on a set of symbolic regression problems. Numerical results show that BBP has a good capability of structure and coefficient optimization with high computational efficiency. (C) 2017 Elsevier B.V. All rights reserved.

关键词Symbolic Regression Separable Function Block Building Programming Genetic Programming
DOI10.1016/j.neucom.2017.10.047
收录类别SCI ; EI
语种英语
WOS记录号WOS:000418370200184
关键词[WOS]EVOLUTION
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence
项目资助者National Natural Science Foundation of China(11532014)
论文分区二类/Q1
力学所作者排名1
引用统计
被引频次:3[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://dspace.imech.ac.cn/handle/311007/72232
专题高温气体动力学国家重点实验室
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Chen C,Luo ZT,Jiang ZL. Block building programming for symbolic regression[J]. NEUROCOMPUTING,2018,275:1973-1980.
APA Chen C,Luo ZT,&Jiang ZL.(2018).Block building programming for symbolic regression.NEUROCOMPUTING,275,1973-1980.
MLA Chen C,et al."Block building programming for symbolic regression".NEUROCOMPUTING 275(2018):1973-1980.
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