[1]LI Xingsen,XU Libo,LIU Haitao,et al.A complementary analysis of factor space and extenics and a fusion model for solving problems[J].CAAI Transactions on Intelligent Systems,2022,17(5):990-998.[doi:10.11992/tis.202106016]
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CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
17
Number of periods:
2022 5
Page number:
990-998
Column:
学术论文—人工智能基础
Public date:
2022-09-05
- Title:
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A complementary analysis of factor space and extenics and a fusion model for solving problems
- Author(s):
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LI Xingsen1; XU Libo2; LIU Haitao3; WANG Peizhuang3
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1. Institute of Extenics and Innovation Methods, Guangdong University of Technology, Guangzhou 510006, China;
2. Research Center of Intelligent Computing and Data Management, Ningbo Institute of Technology, Zhejiang University, Ningbo 315100, China;
3. Institute of Intelligence Engineering and Mathematics, Liaoning Technical University, Fuxin 123000, China
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- Keywords:
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factor space; extenics; problem solving; artificial intelligence; big data; model; intelligent mathematics; knowledge management
- CLC:
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TP18
- DOI:
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10.11992/tis.202106016
- Abstract:
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Intelligent problem solving is a challenging and cross-cutting subject in the field of artificial intelligence. To theoretically support the method for solving the open problem with high universality under the background of big data and artificial intelligence technology, we conducted a comparative analysis of factor space and extenics, finding that they have a common mathematical basis and are overlapping and complementarity in the research direction of intelligent solving of problems. Taking the fusion model for solving problems as an example, this paper demonstrates the basic path and feasibility of the cross study of extenics and factor space. We presented the main direction of the cross research of extenics and factor space, and we expounded on the potential advantages and application scope of problem solving in practice. This research will help increase the systematic and intelligent level of problem solving, improve the degree of problem solving from uncertainty, contingency to inevitability, and promote the development of intelligent mathematics—a mathematical branch of intelligent science.