Static to dynamic data mining to improve future predictions of anthropogenic heat flux

点击翻译按钮获取中文摘要

Current modelling of anthropogenic heat fluxes are based on data sets that are representative of the past, rather than the current or future state of city energy systems. However, many of these data sets are regularly updated making it possible to update model representations of energy systems to better capture the influence of those systems on heat fluxes. As an example, satellite data can be used to highlight energy `hotspots' that can be related to anthropogenic activity at a given time and location. Incorporating data sets such as these into the modelling process can give greater accuracy in relating energy system behaviour to anthropogenic heat flux. Through incorporating dynamic data mining into the modelling process, early trends in behaviour change and system changes can be detected and investigated for better projection of current and future energy use.