Divide and Conquer: A Quick Scheme for Symbolic Regression
文献类型：期刊论文
| 作者 | Luo, Changtong1,2 ; Chen, Chen1,2; Jiang, Zonglin1,2; Jiang ZL(姜宗林); Luo ZT(罗长童)
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| 刊名 | INTERNATIONAL JOURNAL OF COMPUTATIONAL METHODS
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| 出版日期 | 2022-10-01 |
| 卷号 | 19期号:08页码:25 |
| 关键词 | Symbolic regression machine learning divide and conquer bi-correlation test mathematical modeling genetic programming |
| ISSN号 | 0219-8762 |
| DOI | 10.1142/S0219876221420020 |
| 通讯作者 | Luo, Changtong(luo@imech.ac.cn) |
| 英文摘要 | Symbolic regression (SR), as a special machine learning method, can produce mathematical models with explicit expressions. It has received increasing attention in recent years. However, finding a concise, accurate expression is still challenging because of its huge search space. In this work, a divide and conquer (D & C) scheme is proposed. It tries to divide the search space into a number of orthogonal sub-spaces based on the separability feature inferred from the sample data (dividing process). For each sub-space, a sub-function is learned (conquering process). The target model function is then reconstructed with the sub-functions according to their separability patterns. To this end, a separability pattern detecting technique, bi-correlation test (Bi-CT), is also proposed. Note that the sub-functions could be determined by any of the existing SR methods, which makes D & C easy to use. The D & C powered SR has been tested on many symbolic regression problems, and the study shows that D & C can help SR to get the target function more quickly and reliably. |
| 资助项目 | National Natural Science Foundation of China[12072353] ; National Natural Science Foundation of China[11532014] |
| WOS研究方向 | Engineering ; Mathematics |
| 语种 | 英语 |
| WOS记录号 | WOS:000904844800002 |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://dspace.imech.ac.cn/handle/311007/91377]  |
| 专题 | 力学研究所_高温气体动力学国家重点实验室 |
| 通讯作者 | Luo, Changtong |
| 作者单位 | 1.Univ Chinese Acad Sci, Sch Engn Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, State Key Lab High Temp Gas Dynam, Inst Mech, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Luo, Changtong,Chen, Chen,Jiang, Zonglin,et al. Divide and Conquer: A Quick Scheme for Symbolic Regression[J]. INTERNATIONAL JOURNAL OF COMPUTATIONAL METHODS,2022,19(08):25. |
| APA | Luo, Changtong,Chen, Chen,Jiang, Zonglin,姜宗林,&罗长童.(2022).Divide and Conquer: A Quick Scheme for Symbolic Regression.INTERNATIONAL JOURNAL OF COMPUTATIONAL METHODS,19(08),25. |
| MLA | Luo, Changtong,et al."Divide and Conquer: A Quick Scheme for Symbolic Regression".INTERNATIONAL JOURNAL OF COMPUTATIONAL METHODS 19.08(2022):25. |
入库方式： OAI收割
来源：力学研究所
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