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A Fuzzy Approach to Environmental Informatics Modeling and Data Classification in Land Selection


Affiliations
1 Department of Information Technology, Advanced Technological Institute, Dehiwala, Sri Lanka
 

The project highlights usability of fuzzy logic for designing and implementation of an intelligent system by principal component analysis for environmental informatics modeling and data classification. However, problem of classifying a number of environmental objects into classes is one of the main problems of data analysis and arises in many areas of environmental informatics. The project contributesa new fuzzy approach for designing and implementation of a fuzzy system by principal component analysis for environmental informatics modeling and data classification.In the first instance of the methodology, it is mapped commonsense knowledge regarding to analysis of lands to a (land selection assessment) questionnaire with interaction of an Architect. The questionnaire will be analyzed by using Principal Component Analysis (PCA) to find dependencies by the fuzzy system based on Principal Component Analysis (PCA). In this sub phase of Fuzzification, it is basically analysis the fuzzy set and membership functions for commonsense knowledge modeling. Boundary values of membership functions has been defined by using output of PCA. Therefore this process can be concluded as a further classification for derived principal components by integrating PCA with fuzzy logic module. Membership functions for physical, functional and social parameters in land selection has been constructed by using the out puts of principal component analyzer. This intelligent land assessment tool based on a questionnaire to identify land types in percentages and dominated land type in archaeological sites. This enable a guide understand, instrumental values, operating values, and weak values of archaeological sites. The project highlights usability of fuzzy logic for designing and implementation of an intelligent system by principal component analysis for environmental informatics modeling and data classification. The system has been evaluated by an intelligent land assessment tool in a sub field of architecture domain of land selection in archaeological sites to come up with land classifications as physical, functional and social.

Keywords

Sugeno Defuzzification, Principal Component Analysis, Tacit Knowledge, Fuzzy logic, Land selection
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  • A Fuzzy Approach to Environmental Informatics Modeling and Data Classification in Land Selection

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Authors

D. S. Kalana Mendis
Department of Information Technology, Advanced Technological Institute, Dehiwala, Sri Lanka

Abstract


The project highlights usability of fuzzy logic for designing and implementation of an intelligent system by principal component analysis for environmental informatics modeling and data classification. However, problem of classifying a number of environmental objects into classes is one of the main problems of data analysis and arises in many areas of environmental informatics. The project contributesa new fuzzy approach for designing and implementation of a fuzzy system by principal component analysis for environmental informatics modeling and data classification.In the first instance of the methodology, it is mapped commonsense knowledge regarding to analysis of lands to a (land selection assessment) questionnaire with interaction of an Architect. The questionnaire will be analyzed by using Principal Component Analysis (PCA) to find dependencies by the fuzzy system based on Principal Component Analysis (PCA). In this sub phase of Fuzzification, it is basically analysis the fuzzy set and membership functions for commonsense knowledge modeling. Boundary values of membership functions has been defined by using output of PCA. Therefore this process can be concluded as a further classification for derived principal components by integrating PCA with fuzzy logic module. Membership functions for physical, functional and social parameters in land selection has been constructed by using the out puts of principal component analyzer. This intelligent land assessment tool based on a questionnaire to identify land types in percentages and dominated land type in archaeological sites. This enable a guide understand, instrumental values, operating values, and weak values of archaeological sites. The project highlights usability of fuzzy logic for designing and implementation of an intelligent system by principal component analysis for environmental informatics modeling and data classification. The system has been evaluated by an intelligent land assessment tool in a sub field of architecture domain of land selection in archaeological sites to come up with land classifications as physical, functional and social.

Keywords


Sugeno Defuzzification, Principal Component Analysis, Tacit Knowledge, Fuzzy logic, Land selection

References