Electricity demand forecasting plays an important role in smart grid expansion planning.In this paper,we present a dynamic GM(1,1) model based on grey system theory and cubic spline function interpolation principle.Us...Electricity demand forecasting plays an important role in smart grid expansion planning.In this paper,we present a dynamic GM(1,1) model based on grey system theory and cubic spline function interpolation principle.Using piecewise polynomial interpolation thought,this model can dynamically predict the general trend of time series data.Combined with low-order polynomial,the cubic spline interpolation has smaller error,avoids the Runge phenomenon of high-order polynomial,and has better approximation effect.Meanwhile,prediction is implemented with the newest information according to the rolling and feedback mechanism and fluctuating error is controlled well to improve prediction accuracy in time-varying environment.Case study using the living electricity consumption data of Jiangsu province in 2008 is presented to demonstrate the effectiveness of the proposed model.展开更多
Based on PSR framework method, the land ecological security evaluation index system of 16 cities of Anhui Province was constructed. The land ecological security value of subsystem in Anhui Province from 2000 to 2011 w...Based on PSR framework method, the land ecological security evaluation index system of 16 cities of Anhui Province was constructed. The land ecological security value of subsystem in Anhui Province from 2000 to 2011 was calculated using the index weight which was determined by the entropy weight method, and land ecological security trend from 2012 to 2017 was forecasted using GM (1,1) model. The results indicated that, the land ecological security index in Anhui Province from 2000 to 2017 was rising on the whole, with the average value increasing from 0.442 in 2000 to 0.450 in 2017, and there was a huge difference among cities; at the same time, the state index and response index of each subsystem of land ecological security also rose. GM ( 1, 1 ) model had high simulation precision and was able to predict the land ecological security level and the de- velopment trend of each subsystem of Anhui Province from 2012 to 2017. The main factors that influenced the land ecological security of Anhui Prov- ince included per capita farmland area, population density, natural growth rate of population, urbanization level, soil coordination degree, agricultur- al mechanization degree, and the area proportion of nature reserve, which are the focus of land ecological security regulation in the future.展开更多
Nowadays,the quality of the air environment is closely related to the health of the ecosystem and the safety of people living. With more and more attention attached to the quality of the air environment,it is imminent...Nowadays,the quality of the air environment is closely related to the health of the ecosystem and the safety of people living. With more and more attention attached to the quality of the air environment,it is imminent to analyze the future development trend of air quality. In this paper,the grey correlation analysis was used to determine the weights of 6 pollution indexes,namely PM10,PM2. 5,SO2,NO2,CO and O3. The fuzzy comprehensive assessment method was applied to determine the air quality eigenvalues H( 2. 145,1. 926,and 1. 805) of Baoding City in 2014-2016,suggesting that the air quality in Baoding is getting better and better. In addition,the grey forecasting model GM( 1,1) was used to forecast and test the air quality of Baoding City. The results show that the prediction is good.展开更多
基金This work has been supported by the National 863 Key Project Grant No. 2008AA042901, National Natural Science Foundation of China Grant No.70631003 and No.90718037, Foundation of Hefei University of Technology Grant No. 2010HGXJ0083.
文摘Electricity demand forecasting plays an important role in smart grid expansion planning.In this paper,we present a dynamic GM(1,1) model based on grey system theory and cubic spline function interpolation principle.Using piecewise polynomial interpolation thought,this model can dynamically predict the general trend of time series data.Combined with low-order polynomial,the cubic spline interpolation has smaller error,avoids the Runge phenomenon of high-order polynomial,and has better approximation effect.Meanwhile,prediction is implemented with the newest information according to the rolling and feedback mechanism and fluctuating error is controlled well to improve prediction accuracy in time-varying environment.Case study using the living electricity consumption data of Jiangsu province in 2008 is presented to demonstrate the effectiveness of the proposed model.
文摘Based on PSR framework method, the land ecological security evaluation index system of 16 cities of Anhui Province was constructed. The land ecological security value of subsystem in Anhui Province from 2000 to 2011 was calculated using the index weight which was determined by the entropy weight method, and land ecological security trend from 2012 to 2017 was forecasted using GM (1,1) model. The results indicated that, the land ecological security index in Anhui Province from 2000 to 2017 was rising on the whole, with the average value increasing from 0.442 in 2000 to 0.450 in 2017, and there was a huge difference among cities; at the same time, the state index and response index of each subsystem of land ecological security also rose. GM ( 1, 1 ) model had high simulation precision and was able to predict the land ecological security level and the de- velopment trend of each subsystem of Anhui Province from 2012 to 2017. The main factors that influenced the land ecological security of Anhui Prov- ince included per capita farmland area, population density, natural growth rate of population, urbanization level, soil coordination degree, agricultur- al mechanization degree, and the area proportion of nature reserve, which are the focus of land ecological security regulation in the future.
基金Supported by the Fund Project for the Youth Engaged in Science and Technology of Colleges and Universities in Hebei Province(QN2016243)
文摘Nowadays,the quality of the air environment is closely related to the health of the ecosystem and the safety of people living. With more and more attention attached to the quality of the air environment,it is imminent to analyze the future development trend of air quality. In this paper,the grey correlation analysis was used to determine the weights of 6 pollution indexes,namely PM10,PM2. 5,SO2,NO2,CO and O3. The fuzzy comprehensive assessment method was applied to determine the air quality eigenvalues H( 2. 145,1. 926,and 1. 805) of Baoding City in 2014-2016,suggesting that the air quality in Baoding is getting better and better. In addition,the grey forecasting model GM( 1,1) was used to forecast and test the air quality of Baoding City. The results show that the prediction is good.