CAS OpenIR
Complexity at Mesoscales: A Common Challenge in Developing Artificial Intelligence
Guo, Li1,2; Wu, Jun3; Li, Jinghai1,2
2019-10-01
Source PublicationENGINEERING
ISSN2095-8099
Volume5Issue:5Pages:924-929
AbstractExploring the physical mechanisms of complex systems and making effective use of them are the keys to dealing with the complexity of the world. The emergence of big data and the enhancement of computing power, in conjunction with the improvement of optimization algorithms, are leading to the development of artificial intelligence (AI) driven by deep learning. However, deep learning fails to reveal the underlying logic and physical connotations of the problems being solved. Mesoscience provides a concept to understand the mechanism of the spatiotemporal multiscale structure of complex systems, and its capability for analyzing complex problems has been validated in different fields. This paper proposes a research paradigm for AI, which introduces the analytical principles of mesoscience into the design of deep learning models. This is done to address the fundamental problem of deep learning models detaching the physical prototype from the problem being solved; the purpose is to promote the sustainable development of AI. (C) 2019 THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company.
KeywordArtificial intelligence Deep learning Mesoscience Mesoscale Complex system
DOI10.1016/j.eng.2019.08.005
Language英语
WOS KeywordDEEP NEURAL-NETWORKS ; COMPROMISE ; PRINCIPLE
Funding ProjectNational Natural Science Foundation of China[91834303]
WOS Research AreaEngineering
WOS SubjectEngineering, Multidisciplinary
Funding OrganizationNational Natural Science Foundation of China
WOS IDWOS:000492056100021
PublisherELSEVIER
Citation statistics
Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ipe.ac.cn/handle/122111/38925
Collection中国科学院过程工程研究所
Corresponding AuthorLi, Jinghai
Affiliation1.Chinese Acad Sci, Inst Proc Engn, State Key Lab Multiphase Complex Syst, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Chem Engn, Beijing 100049, Peoples R China
3.Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing 100044, Peoples R China
Recommended Citation
GB/T 7714
Guo, Li,Wu, Jun,Li, Jinghai. Complexity at Mesoscales: A Common Challenge in Developing Artificial Intelligence[J]. ENGINEERING,2019,5(5):924-929.
APA Guo, Li,Wu, Jun,&Li, Jinghai.(2019).Complexity at Mesoscales: A Common Challenge in Developing Artificial Intelligence.ENGINEERING,5(5),924-929.
MLA Guo, Li,et al."Complexity at Mesoscales: A Common Challenge in Developing Artificial Intelligence".ENGINEERING 5.5(2019):924-929.
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