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Transactions: WSEAS TRANSACTIONS ON COMPUTERS
Transactions ID Number: 53-787
Full Name: D.S.Kalana Mendis
Position: Senior Lecturer
Age: ON
Sex: Male
Address: Department of Information Technology,Advanced Technological Institute, Labuduwa
Country: SRI LANKA
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E-mail address: kalanaatil@mail.com
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Title of the Paper: Fuzzy Principal component Analysis for tacit knowledge modeling
Authors as they appear in the Paper: Asoka S. Karunananda, Udaya Samaratunga
Email addresses of all the authors: asoka@itfac.mrt.ac.lk, udayasamaratunga@gmail.com
Number of paper pages: 12
Abstract: Knowledge modeling is concerned with abstract model mapping using real world domains. Further all knowledge is tacit or rooted in tacit domains. Abstracting is mainly concerned with classification of such knowledge. In this issue statistical techniques can be issued and mainly concerned with multivariate statistical techniques. However using principal component analysis (PCA) as a multivariate technique makes problematic situation due to inability of classifying knowledge. Analysis using PCA is limited up to principal components extracted by PCA. Therefore existing algorithm of PCA to be addressed for modeling knowledge should be modified. This paper presents a novel mechanism for modifying PCA algorithm to address the problem in concerned using Fuzzy Principal component Analysis (FPCA). Here principal components have been used to define intervals for membership function is used. By doing so, knowledge classification is done effectively by constructing fuzzy m!
emberships functions integrated with PCA. The experimental results using Ayurvedic medicine show that our approach is very promising.
Keywords: Fuzzy data; Principal component analysis; Knowledge modeling; Ayurveda medicine;Expert Systems, Fuzzy logic
EXTENSION of the file: .doc
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