Knowledge and data engineering: Fuzzy approach and genetic algorithms for clustering β-Thalassemia of knowledge based diagnosis decision support system
Fuzzy approach plays an important role in Knowledge and Data Engineering, especially for improving the clustering performance in special problems such as medical diagnosis. This technique is not only a powerful method for clustering special tasks but also a useful technique in various areas. Among h...
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th-cmuir.6653943832-524512018-09-04T09:27:21Z Knowledge and data engineering: Fuzzy approach and genetic algorithms for clustering β-Thalassemia of knowledge based diagnosis decision support system Patcharaporn Paokanta Napat Harnpornchai Nopasit Chakpitak Somdet Srichairatanakool Michele Ceccarelli Computer Science Engineering Fuzzy approach plays an important role in Knowledge and Data Engineering, especially for improving the clustering performance in special problems such as medical diagnosis. This technique is not only a powerful method for clustering special tasks but also a useful technique in various areas. Among hybrid approaches of KDE, in this paper, Fuzzy approach and GAs were selected to cluster several transformed β-Thalassemia variables in which this disease is the common genetic disorder found around the world. According to the genetic counselling problems of this disease in Thailand and other countries, the Knowledge Based Diagnosis Decision Support System for Thalassemia was constructed to reduce these problems. The comparison of clustering results of using Fuzzy approach and hybrid techniques on various β-Thalassemia data sets and expert opinion are presented that K-Means clustering obtains the best result with the RMSE 13.0077 from unrecoded variables, on the other hand Fuzzy C-Mean and Fuzzy-GAs obtain the RMSE 13.6235 and 14.3527 from recoded variables, respectively. As these obtained results, other clustering and classification algorithms will be used to improve the results of KDE techniques for implementing Thalassemia Expert System in the future. © 2013 ISSN 1881-803X. 2018-09-04T09:25:27Z 2018-09-04T09:25:27Z 2013-01-16 Journal 1881803X 2-s2.0-84872130677 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84872130677&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/52451 |
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Computer Science Engineering Patcharaporn Paokanta Napat Harnpornchai Nopasit Chakpitak Somdet Srichairatanakool Michele Ceccarelli Knowledge and data engineering: Fuzzy approach and genetic algorithms for clustering β-Thalassemia of knowledge based diagnosis decision support system |
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Fuzzy approach plays an important role in Knowledge and Data Engineering, especially for improving the clustering performance in special problems such as medical diagnosis. This technique is not only a powerful method for clustering special tasks but also a useful technique in various areas. Among hybrid approaches of KDE, in this paper, Fuzzy approach and GAs were selected to cluster several transformed β-Thalassemia variables in which this disease is the common genetic disorder found around the world. According to the genetic counselling problems of this disease in Thailand and other countries, the Knowledge Based Diagnosis Decision Support System for Thalassemia was constructed to reduce these problems. The comparison of clustering results of using Fuzzy approach and hybrid techniques on various β-Thalassemia data sets and expert opinion are presented that K-Means clustering obtains the best result with the RMSE 13.0077 from unrecoded variables, on the other hand Fuzzy C-Mean and Fuzzy-GAs obtain the RMSE 13.6235 and 14.3527 from recoded variables, respectively. As these obtained results, other clustering and classification algorithms will be used to improve the results of KDE techniques for implementing Thalassemia Expert System in the future. © 2013 ISSN 1881-803X. |
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author |
Patcharaporn Paokanta Napat Harnpornchai Nopasit Chakpitak Somdet Srichairatanakool Michele Ceccarelli |
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Patcharaporn Paokanta Napat Harnpornchai Nopasit Chakpitak Somdet Srichairatanakool Michele Ceccarelli |
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Patcharaporn Paokanta |
title |
Knowledge and data engineering: Fuzzy approach and genetic algorithms for clustering β-Thalassemia of knowledge based diagnosis decision support system |
title_short |
Knowledge and data engineering: Fuzzy approach and genetic algorithms for clustering β-Thalassemia of knowledge based diagnosis decision support system |
title_full |
Knowledge and data engineering: Fuzzy approach and genetic algorithms for clustering β-Thalassemia of knowledge based diagnosis decision support system |
title_fullStr |
Knowledge and data engineering: Fuzzy approach and genetic algorithms for clustering β-Thalassemia of knowledge based diagnosis decision support system |
title_full_unstemmed |
Knowledge and data engineering: Fuzzy approach and genetic algorithms for clustering β-Thalassemia of knowledge based diagnosis decision support system |
title_sort |
knowledge and data engineering: fuzzy approach and genetic algorithms for clustering β-thalassemia of knowledge based diagnosis decision support system |
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2018 |
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https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84872130677&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/52451 |
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