Pattern discovery from the seasonal time-series is of importance. Traditionally, most of the algorithms of pattern discovery in time series are similar. A novel mode of time series is proposed which integrates the Gen...Pattern discovery from the seasonal time-series is of importance. Traditionally, most of the algorithms of pattern discovery in time series are similar. A novel mode of time series is proposed which integrates the Genetic Algorithm (GA) for the actual problem. The experiments on the electric power yield sequence models show that this algorithm is practicable and effective.展开更多
A precise understanding of the relationships between the household characteristics and the residential energy consumption is needed to support the implementation of effective top-bottom energy strategies and to improv...A precise understanding of the relationships between the household characteristics and the residential energy consumption is needed to support the implementation of effective top-bottom energy strategies and to improve the prediction of forecasting models.This paper contributes to the present-day discussion and analyses the build-ing factors,socio-demographic variables and appliances contributing to high-energy expenditures(viz.,electrical energy expenditure,thermal energy expenditure and total energy expenditure)in the Italian households.The proposed study builds on an earlier work proposed by the authors,which identified the determinants of the household energy expenditures,based on a nationally representative survey(the“household Budget Survey:mi-crodata for research purposes-2015”performed by the Italian National Institute of Statistics).In particular,the present paper completes and extends the previous research by applying the odds-ratio analysis to the previously identified determinants,in order to identify the factors that led to high electricity consumption(viz.,electrical energy expenditure,thermal energy expenditure and total energy expenditure).In conclusion,this paper aims to providing a more precise understanding of the factors that certainly affect the energy expenditure.展开更多
文摘Pattern discovery from the seasonal time-series is of importance. Traditionally, most of the algorithms of pattern discovery in time series are similar. A novel mode of time series is proposed which integrates the Genetic Algorithm (GA) for the actual problem. The experiments on the electric power yield sequence models show that this algorithm is practicable and effective.
文摘A precise understanding of the relationships between the household characteristics and the residential energy consumption is needed to support the implementation of effective top-bottom energy strategies and to improve the prediction of forecasting models.This paper contributes to the present-day discussion and analyses the build-ing factors,socio-demographic variables and appliances contributing to high-energy expenditures(viz.,electrical energy expenditure,thermal energy expenditure and total energy expenditure)in the Italian households.The proposed study builds on an earlier work proposed by the authors,which identified the determinants of the household energy expenditures,based on a nationally representative survey(the“household Budget Survey:mi-crodata for research purposes-2015”performed by the Italian National Institute of Statistics).In particular,the present paper completes and extends the previous research by applying the odds-ratio analysis to the previously identified determinants,in order to identify the factors that led to high electricity consumption(viz.,electrical energy expenditure,thermal energy expenditure and total energy expenditure).In conclusion,this paper aims to providing a more precise understanding of the factors that certainly affect the energy expenditure.
