Complexity at Mesoscales: A Common Challenge in Developing Artificial Intelligence
文献类型：期刊论文
| 作者 | Guo, Li1,3; Wu, Jun2; Li, Jinghai1,3 |
| 刊名 | ENGINEERING
 |
| 出版日期 | 2019-10-01 |
| 卷号 | 5期号:5页码:924-929 |
| 关键词 | Artificial intelligence Deep learning Mesoscience Mesoscale Complex system |
| ISSN号 | 2095-8099 |
| DOI | 10.1016/j.eng.2019.08.005 |
| 英文摘要 | 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. |
| WOS关键词 | DEEP NEURAL-NETWORKS ; COMPROMISE ; PRINCIPLE |
| 资助项目 | National Natural Science Foundation of China[91834303] |
| WOS研究方向 | Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000492056100021 |
| 出版者 | ELSEVIER |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://ir.ipe.ac.cn/handle/122111/38924]  |
| 专题 | 中国科学院过程工程研究所 |
| 通讯作者 | Li, Jinghai |
| 作者单位 | 1.Chinese Acad Sci, Inst Proc Engn, State Key Lab Multiphase Complex Syst, Beijing 100190, Peoples R China 2.Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing 100044, Peoples R China 3.Univ Chinese Acad Sci, Sch Chem Engn, Beijing 100049, Peoples R China |
| 推荐引用方式 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. |
入库方式： OAI收割
来源：过程工程研究所
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