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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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  • Umar Lawal Dano,etal, (2012) GIS-based analytic hierarchy process as a multicriteria decision analysis instrument: A review, Arabian Journal of Geosciences 6(8), pp.4-10

  • Chen, Q., Integration of data mining techniques and heuristic knowledge in fuzzy logicmodelling of eutrophication in Taihu Lake. Ecological Modelling, 162, pp. 55–67, 2003.

  • Malins, D. &Metternicht, G., Assessing the spatial extent of dryland salinity through fuzzy modelling. Ecological Modelling, 193(3–4), pp. 387–411, 2006.

  • Metternicht, G., Assessing temporal and spatial changes of salinity using fuzzy logic, remote sensing and GIS. Foundation of an expert system. Ecological Modelling, 144, pp. 163–179, 2001.

  • Khalid Eldrandaly, Developing a GIS-Based MCE Site Selection Tool in ArcGIS Using COM Technology, The International Arab Journal of Information Technology, Vol. 10, No. 3, pp. 268- 274,May 2013

  • Van Pelt, M. J. F. (1994). Environment and project appraisal: Lessons from two cases. Annals of Regional Science, 28(1), 55–76

  • Zadeh, L.A., Fuzzy sets. Information and Control, 8, pp. 338–353, 1965.

  • Zhang, L., Liu, Ch., Davis, C.J., Solomon, D.S., Brann, T.B. & Caldwell, L.E., Fuzzy classification of ecological habitats from FIA data. Forest Science, 50(1), pp. 117–127, 2004.

  • Hollert, H., Heise, S., Pudenz, S., Brüggermann, W.A. & Braunbeck, T., Application of a sediment quality triad and different statistical approaches (Hasse Diagrams and Fuzzy Logic) for the comparative evaluation of small streams. Ecotoxicology, 11(5), pp. 311–321, 2002.

  • Pedersen, T.C.M., Baattrup-Pedersen, A. & Madsen, T.V., Effects of stream restoration and management on plant communities in lowland streams. Freshwater Biology, 51, pp.161–179, 2006.

  • Burrough, P.A., Wilson, J.P., van Gaans, P.F.M. & Hansen, A.J., Fuzzy k-means classification of topoclimatic data as an aid to forest mapping in the Greater Yellowstone Area, USA. Landscape Ecology, 16(6), pp. 523–546, 2001.

  • Liu, M. & Samal, A., A fuzzy clustering approach to delineate agroecozones. Ecological Modelling, 149(3), pp. 215–228, 2002.

  • Rao, R.A. & Srinivas, V.V., Regionalization of watersheds by fuzzy cluster analysis. Journal of Hydrology, 318, pp. 57–79, 2006.

  • Chen, Q., Integration of data mining techniques and heuristic knowledge in fuzzy logic modelling of eutrophication in Taihu Lake. Ecological Modelling, 162, pp. 55–67, 2003.

  • Marchini, A. & Marchini, C., A fuzzy logic model to recognise ecological sectors in the lagoon of Venice based on the benthic community. Ecological Modelling, 193(1–2), pp. 105–118, 2006.

  • Mamdani, E.H. &Assilian, S., An experiment in linguistic synthesis with a fuzzy logic ccontroller. International Journal of Man-Machine Studies, 7(1), pp. 1–13, 1975.

  • Sugeno, M., Industrial Applications of Fuzzy Control. Elsevier Science Pub. Co., 1985.

  • Salski, A. & Noell, Ch., Fuzzy linear programming for the optimization of land use scenarios. Advances in Scientifi c Computing, Computational Intelligence and Applications, eds. N. Mastorakis et al. WSES Press, pp. 355–360, 2001.

  • Bone, C., Dragicevic, S. & Roberts, A., A fuzzyconstrained cellular automata model of forest insect infestations. Ecological Modelling, 192(1–2), pp. 107–125, 2006.

  • Chang, C.L., Lo, S.L. & Yu, S.L., Applying fuzzy theory and genetic algorithm to interpolate precipitation. Journal of Hydrology, 314, pp. 92– 104, 2005.

  • Mendis D. S. K., (2016), An approach for recognition of cultural heritage in VelgamRajamahaViharaya- Trincomalee by Intelligent land assessment tool, 9 th Research Conference-Royal Asiatic Society of Sri Lanka, pp.27, Colombo, Sri Lanka

  • Mendis D. S. K., (2017), A new land selection method cultural heritage, 10 th Research Conference-Royal Asiatic Society of Sri Lanka, pp.59, Colombo, Sri Lanka

  • Mendis D. S. K., (2017), A new land selection method cultural heritage, management: Characterizations of intelligent assessment tool, Second Archaeological research symposium pp. 147-149

  • Mendis D. S. K., (2018), Development of Commonsense Knowledge system for the assessment of cultural recognition in KadurugodaViharaya, Jaffna, 11 th Research Conference-Royal Asiatic Society of Sri Lanka, pp.392-394, Colombo, Sri Lanka

  • Mendis D. S. K., (2019), A land assessment tol for cultural heritage in Divaguhawa, 11 th Research Conference-Royal Asiatic Society of Sri Lanka, pp.313-319, Colombo, Sri Lanka

  • Mendis D. S. K., (2017), Development of land selection tool in cultural recognition for ecosystem services provision, International Conference on Multidisciplinary Approaches, Colombo, Sri Lanka, pp. 42.

  • Mendis D. S. K., (2016), An intelligent land assessments tool for the recognition of cultural heritage in archaeological sites: Case study International Research Conference on Humanities and Social Sciences, Colombo, Sri Lanka, pp. 111.

  • Mendis D. S. K., (2017), Development of land selection tool in cultural recognition for ecosystem services provision, International Conference on Multidisciplinary Approaches, Colombo, Sri Lanka, pp. 42.

  • Mendis D. S. K.,(2017), Assessment of cultural heritage in Mantota Raja Maha vihara-Mannar using an intelligent system, SAARC Regional Seminar on Buddhist cultural trails, Colombo,,Sri Lanka, pp.54

  • Mendis D. S. K., (2017), Assessment of Cultural Heritage in MantotaRajamahaViharaya, Mannar using an Intelligent System, Colombo, Sri Lanka, http://saarcculture.org/2017/08/30/saarc-researchseminar- on-buddhist-cultural-trails/

  • Mendis D. S. K., (2018), A land assessment tool for cultural Recognition in Environment sustainable management: Case study of kadurugoda Vihara- Jaffna, International Conference on Multidisciplinary Approaches, Colombo, Sri Lanka, pp. 27

  • Mendis D. S. K., (2018), A Fuzzy system for the Assessment of Cultural Recognition in KadurugodaViharaya-Jaffna, International Research Conference on Humanities and Social Sciences, Colombo, Sri Lanka, pp. 65.

  • Mendis D. S. K., (2018), An assessment of cultural heritage in KadurugodaViharaya- Jaffna, International Conference on Pali and Buddhist studies, Colombo, Sri Lanka, pp. 128-131

  • Mendis D. S. K., (2016), An Intelligent system for land selection in Archaeological sites, International Conference on Multidisciplinary Approaches, Colombo, Sri Lanka, pp. 114.

  • Salski1WIT Transactions on State of the Art in Science and Engineering, Vol 34, 2009.


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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