[1]MIAO Duoqian,ZHANG Qinghua,QIAN Yuhua,et al.From human intelligence to machine implementation model: theories and applications based on granular computing[J].CAAI Transactions on Intelligent Systems,2016,11(6):743-757.[doi:10.11992/tis.201612014]
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From human intelligence to machine implementation model: theories and applications based on granular computing

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 11 Number of periods: 2016 6 Page number: 743-757 Column: 综述 Public date: 2017-01-20
Title:
From human intelligence to machine implementation model: theories and applications based on granular computing
Author(s):
MIAO Duoqian1;  ZHANG Qinghua2;  QIAN Yuhua3;  LIANG Jiye3;  WANG Guoyin2;  WU Weizhi4;  GAO Yang5;  SHANG Lin5;  GU Shenming4;  ZHANG Hongyun1
1. Key Laboratory of Embedded System & Service Computing Ministry of Education, Tongji University, Shanghai 201804, China;
2. Key Laboratory of Computational Intelligence, Chongqing University of Posts and Telecommunications, Chongqing 400065, China;
3. Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan 030006, China;
4. Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province, Zhejiang Ocean University, Zhoushan 316022, China;
5. State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210093, China
Keywords:
artificial intelligence; big data; uncertainty; granular computing; multi-granulation; rough sets; quotient space; cloud model; three-way decisions
CLC:
TP391
DOI:
10.11992/tis.201612014
Abstract:
Artificial intelligence is a new science of researching and developing theories, methods and technologies to simulate and extend the human intelligence, and is regarded as a simulation of human consciousness and thought processes. Granular computing is a novel concept and a new computing paradigm in the current area of intelligent information processing. It is also a multi-granulation methodology of relevant theories, technologies and tools, which are used to research multi-level thought modes, to solve complex problems and to develop information processing models. First, the related granular computing models or methods, by which artificial intelligence simulates human intelligence, were analyzed in this paper. Also, several classical basic structures and mathematical models on granular computing were briefly summarized. Then, both multi-granulation representations and uncertainty measurements on knowledge were reviewed. Finally, the future opportunities and challenges of solving models using granular computing in the era of big data were discussed and prospected.
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