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Based on extended STIRPAT model, this paper econometrically investigates the impacts on carbon emissions from population, consumption and technology in China by using the principal components regressive analysis method. Using urbanization rate as an index of the population structure, the empirical results of China' s carbon emission from 1990 to 2008 demonstrate that the influence on carbon emission...
The paper selects China and Canada as samples respectively on behalf of developing countries and developed countries, according to the data from “the BP World Energy Statistics 2009” and the formula about carbon emissions from calculation handbook which in the UN's Intergovernmental Panel on Climate Change (IPCC) in 2006, the amount of total carbon emissions, per capita carbon emissions and carbon...
Energy consumption and carbon emissions in Iran have risen rapidly in recent years which is not acceptable regarding environmental regulations. Government officials have been trying to resolve this problem, but so far there has been less success. Exergy analysis method is a powerful tool, which has been successfully used for estimating energy utilization efficiencies of countries. In this study, energy...
Because the increasing energy demand have an important impact on economic development, the accurate projection of energy consumption is crucial to the energy policy decision. In this study, artificial neural network (ANN) model is used to estimate the energy consumption for Chongqing in China. The projection is implemented using a feed-forward neural network, trained by back-propagation algorithm...
In this paper, a wavelet-neural-network-based forecast model is developed for energy demand in China. Combining qualitative with quantitative analysis, we analyze some main factors affecting energy demand in China. A first order wavelet-neural network forecasting model with time-delay is established, including population, GDP, variation of industrial structure and energy consumption. The simulation...
This study investigates prediction of oil consumption in Malaysia. Models of oil consumption are developed and validated with respect to training and validation dataset. Available data for Malaysia is annual data from 1982 to 2006 comprises population, GDP per capita, and oil consumption data. Prediction time target is year 2020 which is commonly used by several energy outlook reports. Two models...
Linear regression has been used for many years for forecasting in marketing, management, sales and energy. In this paper, a fuzzy-based approach is applied for the transport energy demand forecasting using socio-economic and transport related indicators. This forecasting is analyzed based on gross domestic product (GDP), population and the number of vehicles together with historical energy data from...
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