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Ramulus Cinnamomi Intelligence Quality Assessment Based on knowledge reduction

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Ramulus Cinnamomi Intelligence Quality Assessment Based on K...

Extension of information entropy-based measures in incomplete information systems

2010 3rd International Conference on Computer and Electrical Engineering(ICCEE 2010)

作者： Jianyang Lin Mingyan Jiang Yajie Xu Zhoumi Kan Department of Pharmacy The First Hospital of China Medical University

According to the traditional morphological classification divide the quality of traditional Chinese medicine Ramulus Cinnamomi into first grade and second grade. Disperse the chromatogram data Ramulus Cinnamomi obtained by criterion inspect and make knowledge reduction. Then it will get the largest liner irrespective vector group. It will get every clustering centre data of Ramulus Cinnamomi with adaptive weight PSO and POWELL optimization. Make the criterion data of Ramulus Cinnamomi as Weibull distribution and make the sample as Normal distribution to calculate similar and ensure the finial similar with similarity ratio. It used lobato integral and Hermite interpolation. This investigation makes good evaluation to the Ramulus Cinnamomi in Guangdong Guangxi Yunnan and Vietnam and high delicacy and anti-jamming.

关键词： Quality Assessment Distributed Clustering Ramulus Cinnamomi knowledge reduction

来源： cnki会议评论

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Journal of Harbin Institute of Technology(New Series) 2005年第5期12卷 544-550页

作者：李仁璞黄道高茂庭 College of Computer Science and Technology Yantai Normal University Yantai 264025 China College of Information East China University of Science and Technology Shanghai 200237 China Dept. of Computer Science and Engineering Shanghai Maritime University Shanghai 200135 China

It is helpful for people to understand the essence of rough set theory to study the concepts and operations of rough set theory from its information view. In this paper we address knowledge expression and knowledge reduction in incomplete infolvnation systems from the information view of rough set theory. First, by extending information entropy-based measures in complete information systems, two new measures of incomplete entropy and incomplete conditional entropy are presented for incomplete information systems. And then, based on these measures the problem of knowledge reduction in incomplete information systems is analyzed and the reduct definitions in incomplete information system and incomplete decision table are proposed respectively. Finally, the reduct definitions based on incomplete entropy and the reduct definitions based on similarity relation are compared. Two equivalent relationships between them are proved by theorems and an in equivalent relationship between them is illustrated by an example. The work of this paper extends the research of rough set theory from information view to incomplete information systems and establishes the theoretical basis for seeking efficient algorithm of knowledge acquisition in incomplete information systems.

关键词： rough set theory information entropy incomplete information system knowledge reduction

Feature Selection Based on Difference and Similitude in Data Mining

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Wuhan University Journal of Natural Sciences 2007年第3期12卷 467-470页

作者： WU Ming YAN Puliu School of Electronic Information Wuhan University Wuhan 430072 Hubei China

Feature selection is the pretreatment of data mining. Heuristic search algorithms are often used for this subject. Many heuristic search algorithms are based on discernibility matrices, which only consider the difference in information system. Because the similar characteristics are not revealed in discernibility matrix, the result may not be the simplest rules. Although differencesimilitude（DS） methods take both of the difference and the similitude into account, the existing search strategy will cause some important features to be ignored. An improved DS based algorithm is proposed to solve this problem in this paper. An attribute rank function, which considers both of the difference and similitude in feature selection, is defined in the improved algorithm. Experiments show that it is an effective algorithm, especially for large-scale databases. The time complexity of the algorithm is O（｜ C ｜^2｜U ｜^2）.

关键词： knowledge reduction feature selection rough set difference set similitude set attribute rank function

Product Evaluation knowledge Acquisition Based on Rough Sets

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Computer Aided Drafting,Design and Manufacturing 2006年第2期16卷 83-87页

作者： XU Xiao-hui TONG Bing-shu Department of Precision Instruments and Mechanoiogy Tsinghua University Beijing 100084 China

The method and steps of acquiring evaluation rules based on the knowledge reduction theory of rough sets is discussed, and the distilling process and approach for the evaluation rules of mechanical product structure design is described by using hydraulic torque converter as an example. Practice shows that this approach to a certain extent simplifies the knowledge base structure and reasoning process in comparison with the case-based reasoning method in the aspect of setting up evaluation rule base and carrying out reasoning to realize the mechanical product evaluation.

关键词： product design evaluation knowledge acquisition rough set knowledge reduction