Knowledge Management System Of Institute of process engineering,CAS
| Complexity at Mesoscales: A Common Challenge in Developing Artificial Intelligence | |
| Guo, Li1,2; Wu, Jun3; Li, Jinghai1,2 | |
| 2019-10-01 | |
| Source Publication | ENGINEERING
 |
| ISSN | 2095-8099 |
| Volume | 5Issue:5Pages:924-929 |
| Abstract | Exploring 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. |
| Keyword | Artificial intelligence Deep learning Mesoscience Mesoscale Complex system |
| DOI | 10.1016/j.eng.2019.08.005 |
| Language | 英语 |
| WOS Keyword | DEEP NEURAL-NETWORKS ; COMPROMISE ; PRINCIPLE |
| Funding Project | National Natural Science Foundation of China[91834303] |
| WOS Research Area | Engineering |
| WOS Subject | Engineering, Multidisciplinary |
| Funding Organization | National Natural Science Foundation of China |
| WOS ID | WOS:000492056100021 |
| Publisher | ELSEVIER |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ipe.ac.cn/handle/122111/38925 |
| Collection | 中国科学院过程工程研究所 |
| Corresponding Author | Li, Jinghai |
| Affiliation | 1.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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