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Based on purely physical information in deep learning optimizes soliton system parameter identification problem.

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Title: Based on purely physical information in deep learning optimizes soliton system parameter identification problem.
Authors: Zhang, Zhiyang1, Liu, Muwei1, Xing, Xiaowei1,2, Zhang, Shuzhuang1,3, zhangshuzhuang@bupt.edu.cn, Yan, Zhenya1,4, zyyan@mmrc.iss.ac.cn, Liu, Wenjun1,5, jungliu@bupt.edu.cn
Source: Computer Methods in Applied Mechanics & Engineering; Apr2025:Part B, Vol. 438, pN.PAG-N.PAG, 1p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 183572688
AccessLevel: 2
PubType: Academic Journal
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  Data: Based on purely physical information in deep learning optimizes soliton system parameter identification problem.
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=183572688
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      – Type: doi
        Value: 10.1016/j.cma.2025.117852
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      – Code: eng
        Text: English
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      – TitleFull: Based on purely physical information in deep learning optimizes soliton system parameter identification problem.
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              Text: Apr2025:Part B
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              Y: 2025
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