从人类智能到机器实现模型——粒计算理论与方法  

From human intelligence to machine implementation model:theories and applications based on granular computing

作　　者：苗夺谦[1] 张清华[2] 钱宇华[3] 梁吉业[3] 王国胤[2] 吴伟志 高阳[5] 商琳[5] 顾沈明 张红云[1] MIAO Duoqian ZHANG Qinghua QIAN Yuhua LIANG Jiye WANG Guoyin WU Weizhi GAO Yang SHANG Lin GU Shenming ZHANG Hongyun(Key Laboratory of Embedded System ＆ Service Computing Ministry of Education, Tongji University, Shanghai 201804, China KeyLaboratory of Computational Intelligence, Chongqing University of Posts and Telecommunications, Chongqing 400065, China Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan 030006, China Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province, Zhejiang Ocean University, Zhoushan 316022, China State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210093, China)

机构地区：[1]同济大学嵌入式系统与服务计算教育部重点实验室,上海201804 [2]重庆邮电大学计算智能重庆市重点实验室,重庆400065 [3]山西大学计算智能与中文信息处理教育部重点实验室,山西太原030006 [4]浙江海洋大学浙江省海洋大数据挖掘与应用重点实验室,浙江舟山316022 [5]南京大学软件新技术国家重点实验室,江苏南京210093

出　　处：《智能系统学报》2016年第6期743-757,共15页CAAI Transactions on Intelligent Systems

基　　金：国家自然科学基金项目(61573255;61673301;61472056;61432011;61572091;61573321;61272021;U1435212;41631179)

摘　　要：人工智能是研究、开发用于模拟、延伸和扩展人的智能的理论、方法、技术及应用系统的一门新的技术科学,是对人的意识、思维过程的模拟。粒计算是当前智能信息处理领域中一种新的概念和计算范式,是研究基于多层次粒结构的思维方式、复杂问题求解、信息处理模式及其相关理论、技术和工具的方法论。本文首先分析了人工智能模拟人脑智能的粒计算模式与方法,其次总结了粗糙集、商空间、模糊集、云模型、三支决策等几种典型的粒计算基本构架与数学模型,然后分析知识的多粒度解析表示与不确定性度量的研究现状,最后展望了粒计算求解模式在大数据时代所面临的机遇与挑战。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.

关 键 词：人工智能 大数据 不确定性 粒计算 多粒度 粗糙集 商空间 模糊集 云模型 三支决策 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]