In order to find the dominant factor of energy efficiency change, this paper uses the modified structural model to analyze energy efficiency change from 1990 to 2012 in Xinjiang. The result shows that the energy effic...In order to find the dominant factor of energy efficiency change, this paper uses the modified structural model to analyze energy efficiency change from 1990 to 2012 in Xinjiang. The result shows that the energy efficiency increase is largely due to energy technological innovation especially by the industrial sector, and the contribution from structural shift is limited. Therefore, we should vigorously support energy-saving technological progress in the industrial sector and develop the modern service industries with lower energy consumption, in order to realize the goal of improving energy efficiency.展开更多
The effective supply of electricity is the basis of ensuring economic development and people's normal life. It is difficult to store electricity, as leading to the production and consumption must be completed simu...The effective supply of electricity is the basis of ensuring economic development and people's normal life. It is difficult to store electricity, as leading to the production and consumption must be completed simultaneously. Therefore, it is of great significance to accurately predict the demand for electricity consumption for the production planning of electricity and the normal operation of the society. In this paper, a hybrid model is constructed to predict the electricity consumption in China. The structural breaks test of monthly electricity consumption in China from January 2010 to December 2016 is carried out by using the structural breaks unit root test. Based on the existence of structura breaks, the electricity consumption data are decomposed into low-frequency and high-frequency components by wavelet model, and the separated low frequency signal and high frequency signal are predicted by autoregressive integrated moving average(ARIMA) and nonlinear autoregressive neural network(NAR), respectively. Therefore the wavelet-ARIMA-NAR hybrid model is constructed. In order to compare the effect of the hybrid model, the structural time series(STS) model is applied to predicting the electricity consumption. The results of prediction error test show that the hybrid model is more accurate for electricity consumption prediction.展开更多
Theoretical results related to properties of a regularized recursive algorithm for estimation of a high dimensional vector of parameters are presented and proved. The recursive character of the procedure is proposed t...Theoretical results related to properties of a regularized recursive algorithm for estimation of a high dimensional vector of parameters are presented and proved. The recursive character of the procedure is proposed to overcome the difficulties with high dimension of the observation vector in computation of a statistical regularized estimator. As to deal with high dimension of the vector of unknown parameters, the regularization is introduced by specifying a priori non-negative covariance structure for the vector of estimated parameters. Numerical example with Monte-Carlo simulation for a low-dimensional system as well as the state/parameter estimation in a very high dimensional oceanic model is presented to demonstrate the efficiency of the proposed approach.展开更多
The simplified D＆L method with special properties required by ideal decomposition method was used to decompose the impact of carbon emission intensity,input-output technology,the final demand structure and the final ...The simplified D＆L method with special properties required by ideal decomposition method was used to decompose the impact of carbon emission intensity,input-output technology,the final demand structure and the final demand level on changes in industrial carbon emissions in China during 1997-2012. The results showed that the final demand level which was the most important factor leading to the growth of carbon emissions performed a steadily and significantly positive and sustained effect. The carbon emissions intensity which was the only factor that led to the reduction in carbon emissions showed a negative effect. The input-output technology showed a positive effect. The final demand structure underwent a transition from a negative effect to a weak positive effect and finally to a positive effect. In order to achieve the goal of total carbon emission control,China should take some measures such as reducing direct carbon emission coefficient to strengthen the negative impact of carbon emission intensity. Meanwhile,China should implement some structural adjustment measures such as optimizing the final demand structure and reducing the proportion of industries with a great increase of influence coefficient to change the input-output technology and the final demand structure from the positive effect to the negative effect.展开更多
基金supported by the National Natural Science Foundation of China (Grant No.71463057)the Young Innovative Talent Training Project of Xinjiang Uygur Autonomous Region (Grant No. 2013731005)+1 种基金the Natural Science Foundation of Xinjiang Uygur Autonomous Region (Grant No. 2012211B02)the Humanities and Social Science Project of Ministry of Education of China (Grant No. 11YJC790148)
文摘In order to find the dominant factor of energy efficiency change, this paper uses the modified structural model to analyze energy efficiency change from 1990 to 2012 in Xinjiang. The result shows that the energy efficiency increase is largely due to energy technological innovation especially by the industrial sector, and the contribution from structural shift is limited. Therefore, we should vigorously support energy-saving technological progress in the industrial sector and develop the modern service industries with lower energy consumption, in order to realize the goal of improving energy efficiency.
基金National Social Science Foundation of China(No.18AGL028)Social Science Foundation of the Higher Education Institutions of Jiangsu Province,China(No.2018SJZDI070)Social Science Foundations of the Jiangsu Province,China(Nos.16ZZB004,17ZTB005)
文摘The effective supply of electricity is the basis of ensuring economic development and people's normal life. It is difficult to store electricity, as leading to the production and consumption must be completed simultaneously. Therefore, it is of great significance to accurately predict the demand for electricity consumption for the production planning of electricity and the normal operation of the society. In this paper, a hybrid model is constructed to predict the electricity consumption in China. The structural breaks test of monthly electricity consumption in China from January 2010 to December 2016 is carried out by using the structural breaks unit root test. Based on the existence of structura breaks, the electricity consumption data are decomposed into low-frequency and high-frequency components by wavelet model, and the separated low frequency signal and high frequency signal are predicted by autoregressive integrated moving average(ARIMA) and nonlinear autoregressive neural network(NAR), respectively. Therefore the wavelet-ARIMA-NAR hybrid model is constructed. In order to compare the effect of the hybrid model, the structural time series(STS) model is applied to predicting the electricity consumption. The results of prediction error test show that the hybrid model is more accurate for electricity consumption prediction.
文摘Theoretical results related to properties of a regularized recursive algorithm for estimation of a high dimensional vector of parameters are presented and proved. The recursive character of the procedure is proposed to overcome the difficulties with high dimension of the observation vector in computation of a statistical regularized estimator. As to deal with high dimension of the vector of unknown parameters, the regularization is introduced by specifying a priori non-negative covariance structure for the vector of estimated parameters. Numerical example with Monte-Carlo simulation for a low-dimensional system as well as the state/parameter estimation in a very high dimensional oceanic model is presented to demonstrate the efficiency of the proposed approach.
基金Supported by General Project for Humanities and Social Sciences Research of Ministry of Education of China(10YJC790025)Philosophy and Social Sciences Planning Project of Zhejiang Province(10CGJJ12YBQ)
文摘The simplified D＆L method with special properties required by ideal decomposition method was used to decompose the impact of carbon emission intensity,input-output technology,the final demand structure and the final demand level on changes in industrial carbon emissions in China during 1997-2012. The results showed that the final demand level which was the most important factor leading to the growth of carbon emissions performed a steadily and significantly positive and sustained effect. The carbon emissions intensity which was the only factor that led to the reduction in carbon emissions showed a negative effect. The input-output technology showed a positive effect. The final demand structure underwent a transition from a negative effect to a weak positive effect and finally to a positive effect. In order to achieve the goal of total carbon emission control,China should take some measures such as reducing direct carbon emission coefficient to strengthen the negative impact of carbon emission intensity. Meanwhile,China should implement some structural adjustment measures such as optimizing the final demand structure and reducing the proportion of industries with a great increase of influence coefficient to change the input-output technology and the final demand structure from the positive effect to the negative effect.
