Start Date
1-10-2013 10:35 AM
End Date
1-10-2013 11:00 AM
Description
Abstract: The socio-economic development and liveability of a region are affected to a great extent by the region's infrastructure services. Data-driven forecasting the demands for infrastructure utilities (for example, electricity, water, and waste) of a region becomes a challenging issue in the situation of highly integrative infrastructure networks and restricted data sharing, which involves handling temporary and spatial infrastructure utility data simultaneously and modelling the correlations between different infrastructure utilities and their interactions with relevant socio-economic and environmental indicators. Data mining and complex fuzzy set techniques are used to implement this kind of analytical capability in SMART Infrastructure Dashboard (SID). The developed forecasting method and technique can be used by local governmental agencies, infrastructure service designers and providers, and local communities for better governance, planning and delivering of effective and efficient infrastructure service and facility. It can also provide support evidence for a region’s long-term sustainable planning and development.
Citation:
Ma, J., Wickramasuniya, R., Perez, P. & Safadi, M. (2014). Data-Driven Forecasts of Regional Demand for Infrastructure Services. In: Campbell P. and Perez P. (Eds), Proceedings of the International Symposium of Next Generation Infrastructure, 1-4 October 2013, SMART Infrastructure Facility, University of Wollongong, Australia.
Data-Driven Forecasts of Regional Demand for Infrastructure Services
Abstract: The socio-economic development and liveability of a region are affected to a great extent by the region's infrastructure services. Data-driven forecasting the demands for infrastructure utilities (for example, electricity, water, and waste) of a region becomes a challenging issue in the situation of highly integrative infrastructure networks and restricted data sharing, which involves handling temporary and spatial infrastructure utility data simultaneously and modelling the correlations between different infrastructure utilities and their interactions with relevant socio-economic and environmental indicators. Data mining and complex fuzzy set techniques are used to implement this kind of analytical capability in SMART Infrastructure Dashboard (SID). The developed forecasting method and technique can be used by local governmental agencies, infrastructure service designers and providers, and local communities for better governance, planning and delivering of effective and efficient infrastructure service and facility. It can also provide support evidence for a region’s long-term sustainable planning and development.
Citation:
Ma, J., Wickramasuniya, R., Perez, P. & Safadi, M. (2014). Data-Driven Forecasts of Regional Demand for Infrastructure Services. In: Campbell P. and Perez P. (Eds), Proceedings of the International Symposium of Next Generation Infrastructure, 1-4 October 2013, SMART Infrastructure Facility, University of Wollongong, Australia.