Abstract
Energy consumption per unit of GDP, reflecting the environmental costs of economic development, pointed out the direction for urban construction, environmental protection is our common responsibility. In real life, the impact of energy consumption per unit of GDP is complex and uncertain factors, according to a series of known and unknown information, we can predict the energy consumption per unit of GDP as a grey system, so you can use the grey system theory. Grey model requires only a limited amount of data to estimate the unknown system behavior. In this study, first of all, by using the known data we established GM (1, 1) model, Verhulst model and the DGM (2, 1) model predictive analysis. The results show that GM (1, 1) model’s prediction accuracy is higher than the prediction accuracy of Verhulst model and DGM (2, 1) model. Then, Shanghai next unit GDP energy consumption is predicted by GM (1, 1) model.
Highlights
Community in the development process will certainly be different levels of energy consumption and Shanghai as the center of China's economic development, economic development has been in a leading position, while Shanghai is practical action to efforts to achieve energy reduction targets
The unit GDP energy consumption of many factors, but there are many uncertain factors effect, but according to the relevant statistical indicators, or to the relevant statistical indicators derived on the basis of scientific prediction
Grey models: Generally, it consists of three parts in the GM (1, 1) modeling: preprocessing data by AGO (Accumulation Generating Operation), which is to reduce the randomness inherent in data; data estimation with first-order difference equation, is solved where two parameters, developing coefficient and grey input; post-processing by IAGO (Inverse Accumulated Generation Operation) to explore the final estimate
Summary
Community in the development process will certainly be different levels of energy consumption and Shanghai as the center of China's economic development, economic development has been in a leading position, while Shanghai is practical action to efforts to achieve energy reduction targets. According to the Shanghai Bureau of Statistics data, we can develop Shanghai unit GDP energy consumption showed a clear downward trend. He et al (2009) had used grey system theory to take a new approach to performance analysis of ejector refrigeration system. Huang et al (2011) had used grey system theory and multivariate linear regression to study the application and research of a new combinatorial analysis and forecasting method in real estate area. Guo et al (2011) had used grey system theory to study a new approach to energy consumption prediction of domestic heat pump water heater. Li et al (2012) had used grey system theory to study a new approach to performance analysis of disinfection. Corresponding Author: Hongyan Li, College of Management, Shanghai University of Engineering Science, Shanghai 201620, China 7
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