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A multilevel block building algorithm for fast modeling generalized separable systems
Chen C(陈辰); Luo ZT(罗长童); Jiang ZL(姜宗林)
Source PublicationEXPERT SYSTEMS WITH APPLICATIONS
2018-11-01
Volume109Pages:25-34
ISSN0957-4174
Abstract

Symbolic regression is an important application area of genetic programming (GP), aimed at finding an optimal mathematical model that can describe and predict a given system based on observed input response data. However, GP convergence speed towards the target model can be prohibitively slow for large-scale problems containing many variables. With the development of artificial intelligence, convergence speed has become a bottleneck for practical applications. In this paper, based on observations of real-world engineering equations, generalized separability is defined to handle repeated variables that appear more than once in the target model. To identify the structure of a function with a possible generalized separability feature, a multilevel block building (MBB) algorithm is proposed in which the target model is decomposed into several blocks and then into minimal blocks and factors. The minimal factors are relatively easy to determine for most conventional GP or other non-evolutionary algorithms. The efficiency of the proposed MBB has been tested by comparing it with Eureqa, a state-of-the-art symbolic regression tool. Test results indicate MBB is more effective and efficient; it can recover all investigated cases quickly and reliably. MBB is thus a promising algorithm for modeling engineering systems with separability features. (C) 2018 Elsevier Ltd. All rights reserved.

KeywordSymbolic Regression Genetic Programming Generalized Separability Multilevel Block Building
DOI10.1016/j.eswa.2018.05.021
URL查看原文
Indexed BySCI ; EI
Language英语
WOS IDWOS:000437069700003
WOS KeywordSymbolic Regression ; Genetic Algorithm ; Simplification ; Identification ; Evolution ; Circuits
WOS Research AreaComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Operations Research & Management Science
WOS SubjectComputer Science ; Engineering ; Operations Research & Management Science
Funding OrganizationNational Natural Science Foundation of China [11532014]
Classification二类/q1
Ranking1
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Document Type期刊论文
Identifierhttp://dspace.imech.ac.cn/handle/311007/77862
Collection高温气体动力学国家重点实验室
Corresponding AuthorLuo ZT(罗长童)
Affiliation1.Chinese Acad Sci, Inst Mech, State Key Lab High Temp Gas Dynam, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Engn Sci, Beijing 100049, Peoples R China
Recommended Citation
GB/T 7714
Chen C,Luo ZT,Jiang ZL. A multilevel block building algorithm for fast modeling generalized separable systems[J]. EXPERT SYSTEMS WITH APPLICATIONS,2018,109:25-34.
APA Chen C,Luo ZT,&Jiang ZL.(2018).A multilevel block building algorithm for fast modeling generalized separable systems.EXPERT SYSTEMS WITH APPLICATIONS,109,25-34.
MLA Chen C,et al."A multilevel block building algorithm for fast modeling generalized separable systems".EXPERT SYSTEMS WITH APPLICATIONS 109(2018):25-34.
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