Conference Paper

Neuro Fuzzy Classification and Detection Technique for Bioinformatics Problems

Dept. of Control & Instrum., Univ. Teknologi Malaysia, Skudai
DOI: 10.1109/AMS.2007.70 Conference: Modelling & Simulation, 2007. AMS '07. First Asia International Conference on
Source: IEEE Xplore

ABSTRACT

Bioinformatics is an emerging science and technology which has lots of research potential in the future. It involves multi-interdisciplinary approaches such as mathematics, physics, computer science and engineering, biology, and behavioral science. Computers are used to gather, store, analyze as well as integration of patterns and biological data information which can then be applied to discover new useful diagnosis or information. In this study, the focus was directed to the classification or clustering techniques which can be applied in the bioinformatics fields based on the Sugeno type neuro fuzzy model or ANFIS (adaptive neuro fuzzy inference system). It is very important to identify new integration of classification or clustering algorithm especially in neuro fuzzy domain as compared to conventional or traditional method. This paper explores the suitability and performance of recurrent classification technique, fuzzy c means (FCM) act as classifier in neuro fuzzy system compared to subclustering method. A package of software based on neuro fuzzy model (ANFIS) has been developed using MATLAB software and optimization were done with the help from WEKA. A set diabetes data based on real diagnosis of patient was used

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Available from: Fauzi Othman, Feb 06, 2014
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    • "The algorithm fuzzy c-means (FCM) is a typical clustering algorithm, which was used in a wide variety of engineering and scientific disciplines such as modeling[7]the decision[8], pattern recognition and classification[9], segmentation[10]. Recently the classification with the approach FCM-ANFIS[11]was applied on database of diabetes collected by the Faculty of Computer Science and Information, University of Technology Malaysia; the results have reached 72.66%. The remainder of the paper is organized as follows, the Adaptive Neuro-Fuzzy Inference System (ANFIS) is proposed based on the model of Takagi-Sugeno. "

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