The Study Of China's Energy Consumption Forecasting Based On Genetic Grey-network Theory

Energy is the foundation of human society to survive,and it is the basic driving force in world economic development now.Scientific prediction of China's future energy consumption growth will provide a basis for decision-making departments to carry out the energy planning work.This thesis analysed China's energy consumption and it's influencing factors.Based on the combination forecast model theory to build up the gray neural network model.The genetic algorithm is used to optimize the model design in order to find the optimal parameter combination.The contents of this thesis are summarized as following:1.Based on the collection of the China's energy and socioeconomic statistical data,the grey relation theory was used to calculate the influence degree of each influence factor on energy consumption.and multiple correlation method was used to calculate the correlation between the factors.2.Based on the grey system theory,we build up GM and pGM model.After analysis and comparison,pGM model was chosen as grey part of the combination model.The combination model can learn the long term certain growth trend of energy consumption by pGM.In addition,considering the stochastic variability of the energy consumption time series,BP neural network model was used to analyze the model.And the genetic algorithm(ga)was used to optimize the weight(threshold)combination of neural network.3.gaBP-pGM model was used to predict the trend of China's energy consumption growth in 2016-2020 and the total energy consumption in 2050.The result shows that if there were a planned growth of economic indictors in 2016-2020,energy consumption would increase steadily.the energy consumption will 4.874 billion tons of standard coal in 2020 and 8.914 billion tons of standard coal in 2050.Energy consumption will not break up the upper limit of plan in 2020.And the next 35 years(2016-2050).energy consumption will increase each year 130 million tons of standard coal,less than in the past 15 years(2000-2015)of 190 million tons of annual growth rate.