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A conceptual method for modeling residential utility consumption using complex fuzzy sets

Conference Paper


Abstract


  • In many countries including Australia, residential utility consumption, as a primary measurement of infrastructure service at local and state levels, is affected by many influential factors such as different varieties of utilities, local community profiles and regional climate conditions. Due to the fact that the information of a regional residential utility consumptions and their influential factors are often held separately by different public and private agencies, there is an urgent need among the communities, the utility providers, and the utility administration organizations for an integrated view on local residential utility consumption and usage for better utility service and governance. Developing such an integrated view is challenging due to the dispersion of relevant data sets at various temporal and spatial scales and the underlying complexity of increasingly interacting factors. By using complex fuzzy sets to describe uncertainty and periodicity features at various temporal and spatial scales, this paper presents a conceptual method for modeling residential utility consumption in the development of a geographic-business intelligence-based infrastructure information platform. Through the presented method, cross-organization residential utility consumption pattern can be extracted through a knowledge-based pattern mining technique. This work can be used for providing an integrated view on the entire infrastructure service to support

    relevant decision making.

Publication Date


  • 2013

Citation


  • Ma, J., Wickramasuriya, R., Safadi, M., Davies, T. & Perez, P. (2013). A conceptual method for modeling residential utility consumption using complex fuzzy sets. In W. Pedrycz & M. Z. Reformat (Eds.), Proceedings of the Joint World Congress and NAFIPS Annual Meeting (pp. 1227-1232). United States: IEEE.

Scopus Eid


  • 2-s2.0-84886501318

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/1622

Start Page


  • 1227

End Page


  • 1232

Abstract


  • In many countries including Australia, residential utility consumption, as a primary measurement of infrastructure service at local and state levels, is affected by many influential factors such as different varieties of utilities, local community profiles and regional climate conditions. Due to the fact that the information of a regional residential utility consumptions and their influential factors are often held separately by different public and private agencies, there is an urgent need among the communities, the utility providers, and the utility administration organizations for an integrated view on local residential utility consumption and usage for better utility service and governance. Developing such an integrated view is challenging due to the dispersion of relevant data sets at various temporal and spatial scales and the underlying complexity of increasingly interacting factors. By using complex fuzzy sets to describe uncertainty and periodicity features at various temporal and spatial scales, this paper presents a conceptual method for modeling residential utility consumption in the development of a geographic-business intelligence-based infrastructure information platform. Through the presented method, cross-organization residential utility consumption pattern can be extracted through a knowledge-based pattern mining technique. This work can be used for providing an integrated view on the entire infrastructure service to support

    relevant decision making.

Publication Date


  • 2013

Citation


  • Ma, J., Wickramasuriya, R., Safadi, M., Davies, T. & Perez, P. (2013). A conceptual method for modeling residential utility consumption using complex fuzzy sets. In W. Pedrycz & M. Z. Reformat (Eds.), Proceedings of the Joint World Congress and NAFIPS Annual Meeting (pp. 1227-1232). United States: IEEE.

Scopus Eid


  • 2-s2.0-84886501318

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/1622

Start Page


  • 1227

End Page


  • 1232