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Financial security evaluation of the electric power industry in China based on a back propagation neural network optimized by genetic algorithm

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  • Sun, Wei
  • Xu, Yanfeng

Abstract

Recently security issues like investment and financing in China's power industry have become increasingly prominent, bringing serious challenges to the financial security of the domestic power industry. Thus, it deserves to develop financial safety evaluation towards the Chinese power industry and is of practical significance. In this paper, the GA (genetic algorithm) is used to optimize the connection weights and thresholds of the traditional BPNN (back propagation neural network) so the new model of BPNN based on GA is established, hereinafter referred to as GA-BPNN (back propagation neural network based on genetic algorithm). Then, an empirical example of the electric power industry in China during the period 2003–2010 was selected to verify the proposed algorithm. By comparison with three other algorithms, the results indicate the model can be applied to evaluate the financial security of China's power industry effectively. Then index values of the financial security of China's power industry in 2011 were obtained according to the tested prediction model and the comprehensive safety scores and grades are calculated by the weighted algorithm. Finally, we analyzed the reasons and throw out suggestions based on the results. The work of this paper will provide a reference for the financial security evaluation of the energy industry in the future.

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  • Sun, Wei & Xu, Yanfeng, 2016. "Financial security evaluation of the electric power industry in China based on a back propagation neural network optimized by genetic algorithm," Energy, Elsevier, vol. 101(C), pages 366-379.
    • Handle: RePEc:eee:energy:v:101:y:2016:i:c:p:366-379
    DOI: 10.1016/j.energy.2016.02.046
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    as
    1. Cheung, Brian C. & Carriveau, Rupp & Ting, David S.K., 2014. "Multi-objective optimization of an underwater compressed air energy storage system using genetic algorithm," Energy, Elsevier, vol. 74(C), pages 396-404.
    2. Yu, Feng & Xu, Xiaozhong, 2014. "A short-term load forecasting model of natural gas based on optimized genetic algorithm and improved BP neural network," Applied Energy, Elsevier, vol. 134(C), pages 102-113.
    3. Foo, K.Y., 2015. "A vision on the opportunities, policies and coping strategies for the energy security and green energy development in Malaysia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1477-1498.
    4. Xie, Bai-Chen & Shang, Li-Feng & Yang, Si-Bo & Yi, Bo-Wen, 2014. "Dynamic environmental efficiency evaluation of electric power industries: Evidence from OECD (Organization for Economic Cooperation and Development) and BRIC (Brazil, Russia, India and China) countrie," Energy, Elsevier, vol. 74(C), pages 147-157.
    5. Ryu, Hanee & Dorjragchaa, Shonkhor & Kim, Yeonbae & Kim, Kyunam, 2014. "Electricity-generation mix considering energy security and carbon emission mitigation: Case of Korea and Mongolia," Energy, Elsevier, vol. 64(C), pages 1071-1079.
    6. Ang, B.W. & Choong, W.L. & Ng, T.S., 2015. "A framework for evaluating Singapore’s energy security," Applied Energy, Elsevier, vol. 148(C), pages 314-325.
    7. Jewell, Jessica & Cherp, Aleh & Riahi, Keywan, 2014. "Energy security under de-carbonization scenarios: An assessment framework and evaluation under different technology and policy choices," Energy Policy, Elsevier, vol. 65(C), pages 743-760.
    8. Neves, Diana & Silva, Carlos A., 2015. "Optimal electricity dispatch on isolated mini-grids using a demand response strategy for thermal storage backup with genetic algorithms," Energy, Elsevier, vol. 82(C), pages 436-445.
    9. Hang, Leiming & Tu, Meizeng, 2007. "The impacts of energy prices on energy intensity: Evidence from China," Energy Policy, Elsevier, vol. 35(5), pages 2978-2988, May.
    10. Glynn, James & Chiodi, Alessandro & Gargiulo, Maurizio & Deane, J.P. & Bazilian, Morgan & Gallachóir, Brian Ó, 2014. "Energy Security Analysis: The case of constrained oil supply for Ireland," Energy Policy, Elsevier, vol. 66(C), pages 312-325.
    11. Taghavifar, Hadi & Khalilarya, Shahram & Jafarmadar, Samad, 2014. "Diesel engine spray characteristics prediction with hybridized artificial neural network optimized by genetic algorithm," Energy, Elsevier, vol. 71(C), pages 656-664.
    12. Sencar, Marko & Pozeb, Viljem & Krope, Tina, 2014. "Development of EU (European Union) energy market agenda and security of supply," Energy, Elsevier, vol. 77(C), pages 117-124.
    13. Wu, Kang, 2014. "China׳s energy security: Oil and gas," Energy Policy, Elsevier, vol. 73(C), pages 4-11.
    14. Gracceva, Francesco & Zeniewski, Peter, 2014. "A systemic approach to assessing energy security in a low-carbon EU energy system," Applied Energy, Elsevier, vol. 123(C), pages 335-348.
    15. Islam, Aminul & Chan, Eng-Seng & Taufiq-Yap, Yun Hin & Mondal, Md. Alam Hossain & Moniruzzaman, M. & Mridha, Moniruzzaman, 2014. "Energy security in Bangladesh perspective—An assessment and implication," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 154-171.
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