Data Mining, Simulation and Operational Statistics for Real Time Dynamic Decision Making for Next Generation Infrastructure
Start Date
3-10-2013 3:00 PM
End Date
3-10-2013 3:25 PM
Description
Abstract: Meeting the need of increasing population, decreasing natural resources (energy, water, clean air, land, minerals, climate, natural vegetation flora forma, ocean, marine life, ecosystems) while maintaining increasing living standards, requires a system with optimum productivity and resource allocation capabilities. In order to model such complex system one needs to establish a real time data and information gathering platform in position (latitude, longitude, altitude) and time domain. This provides the big data source for data mining analysis and to produce real time analytical tools for better informed decision making. Simulation builds, validates and utilise the model to evaluate the impact of proposed operating strategies on performance indicators for better decision making. In operational statistics, one integrates the estimation and the optimization tasks to estimate the optimal policy directly. Traditional approach which separates the estimation and the optimization tasks can lead to suboptimal solution. These methods will be demonstrated using inventory control application.
Citation:
Liyanage-Hansen, L. (2014). Data Mining, Simulation and Operational Statistics for Real Time Dynamic Decision Making for Next Generation Infrastructure. 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 Mining, Simulation and Operational Statistics for Real Time Dynamic Decision Making for Next Generation Infrastructure
Abstract: Meeting the need of increasing population, decreasing natural resources (energy, water, clean air, land, minerals, climate, natural vegetation flora forma, ocean, marine life, ecosystems) while maintaining increasing living standards, requires a system with optimum productivity and resource allocation capabilities. In order to model such complex system one needs to establish a real time data and information gathering platform in position (latitude, longitude, altitude) and time domain. This provides the big data source for data mining analysis and to produce real time analytical tools for better informed decision making. Simulation builds, validates and utilise the model to evaluate the impact of proposed operating strategies on performance indicators for better decision making. In operational statistics, one integrates the estimation and the optimization tasks to estimate the optimal policy directly. Traditional approach which separates the estimation and the optimization tasks can lead to suboptimal solution. These methods will be demonstrated using inventory control application.
Citation:
Liyanage-Hansen, L. (2014). Data Mining, Simulation and Operational Statistics for Real Time Dynamic Decision Making for Next Generation Infrastructure. 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.