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Analysis of the trend of global power sources based on comment emotion mining

Global Energy Interconnection 2020年第3期3卷 283-291页

作者： Shengxiang Zhang Chao Shi Xin Jiang Ying Zhang Lu Zhang Global Energy Interconnection Development and Cooperation Organization No.8 Xuanwumennei StreetBeijing 100031P.R.China POWERCHINA Changchun Electric Power Engineering Co. Ltd.Changchun CityJilin Province130062P.R.China Nanrui Group Co. Ltd.Chenxin StreetNanjingJiangsu Province210003P.R.China aktins The Axis10 Holliday StreetBirminghamB11TFUnited Kingdom

In recent years,renewable energy technologies have been developed vigorously,and related supporting policies have been *** developmental trend of different energy sources directly affects the future developmental pattern of the energy and power *** trend research can be quantified through data statistics and model calculations;however,parameter settings and optimization are difficult,and the analysis results sometimes do not reflect objective *** paper proposes an energy and power information analysis method based on emotion *** method collects energy commentary news and literature reports from many authoritative media around the world and builds a convolutional neural network model and a text analysis model for topic classification and positive/negative emotion evaluation,which helps obtain text evaluation matrixes for all collected ***,a long-short-term memory model algorithm is employed to predict the future development prospects and market trends for various types of energy based on the analyzed emotions in different time *** results indicate that energy trend analysis based on this method is consistent with the real scenario,has good applicability,and can provide a useful reference for the development of energy and power resources and of other industry areas as well.

关键词： Global energy and power trend Topic classification Text emotion analysis CNN LSTM

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