Objective Modeling and Analysis of Interstate Energy Contract

Jinghan Wang, Suiyu Zhang, Yanjun Li

Shandong university of science and technology, Qingdao campus, Qingdao, 266590

Abstract: First, selects four indices, the development of energy in four states: climate, heat transfer factor, GDP, population, and genetic algorithm GEAT verified the rationality of the choice, so that improved LSTM deep recurrent neural network good generalization ability to forecast, and the establishment of four state energy rating model to predict the quantitative results. Second, consumption is regarded as the best user criterion for renewable energy evaluation. The TOPSIS method is used to sort them and get the best performance of CA in 2009. Then used DEA to verify it, it was found well.

Keywords: GEAT genetic algorithm; LSTM deep recurrent neural network; TOPSIS evaluation method; DEA Data Envelopment Method