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

Sun, Wei; Xu, Yanfeng

doi:10.1016/j.energy.2016.02.046

Cited by 62 publications

(36 citation statements)

References 28 publications

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“…A (1) will be the optimum selection if above two conditions are satisfied. Moreover, if one of the terms is not qualified, some compromise terms are provided:…”

Section: Vikor Comprehensive Assessment Modelmentioning

confidence: 99%

“…where Q(A (1) ) and Q(A (2) ) demonstrate alternatives ranking the first and second in accordance with Q j values.…”

Section: Vikor Comprehensive Assessment Modelmentioning

confidence: 99%

“…(1) If only the first qualification is met, both A (1) and A (2) are the optimal selection. (2) If the first term cannot be qualified and only the second one is met, the alternatives that cannot adhere to the first one are the compromise selections.…”

Section: Vikor Comprehensive Assessment Modelmentioning

confidence: 99%

“…The electricity industry is a significant supporting industry, which has a great influence on national economic growing and energy security [1,2]. As a critical part of the entire power industry chain, power grid corporations undertake the important responsibility of connecting the power generation and power consuming terminals, which plays a primary role in electric grid construction, stable electricity supply, and electric universal service [3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

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Comprehensive Performance Evaluation of Electricity Grid Corporations Employing a Novel MCDM Model

Zhao

Guo

2018

Sustainability

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Abstract:Under the new round reform of electricity market in China, a large amount of electricity sales companies has emerged in some provinces, and the reform of transmission and distribution tariffs is also in progress. Electricity grid corporations are required to update their operational strategies and improve comprehensive performance to adapt to the fierce competition in the electricity market. Considering this, a novel MCDM (multi-criteria decision making) model integrating Fuzzy-Delphi, the best-worst method (BWM), the entropy weight calculation approach, and the VIKOR method is established in this investigation to assess the comprehensive performances of five selected provincial electricity grid corporations. The comprehensive performance assessment indicator system is constructed in accordance with Fuzzy-Delphi approach, composed of 21 significant sub-criteria from the aspects of profitability capacity, development capacity, safety production capacity, electricity supply reliability, outstanding service provision, energy conservation, and environmental protection. The sub-criteria weights are computed by combining subjective weights determined by BWM and objective weights computed by the entropy weight calculation approach. The comprehensive performance evaluation model is established based on VIKOR. As the electricity grid corporation A is superior in profitability capacity (especially in electricity sales amount) and safety production capacity criterion, it is superior over other four electricity grid corporations. The established novel MCDM is practical and rational, which is applicable for electricity grid corporations' comprehensive performance evaluation.

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“…A (1) will be the optimum selection if above two conditions are satisfied. Moreover, if one of the terms is not qualified, some compromise terms are provided:…”

Section: Vikor Comprehensive Assessment Modelmentioning

confidence: 99%

“…where Q(A (1) ) and Q(A (2) ) demonstrate alternatives ranking the first and second in accordance with Q j values.…”

Section: Vikor Comprehensive Assessment Modelmentioning

confidence: 99%

Section: Vikor Comprehensive Assessment Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Comprehensive Performance Evaluation of Electricity Grid Corporations Employing a Novel MCDM Model

Zhao

Guo

2018

Sustainability

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“…The electric power industry is a pillar industry that affects national energy security and economic development [1,2]. Power grid enterprises are a very important part of the electricity industry chain, which undertake several important functions, such as power grid construction, safe and stable power supply, and universal electric service [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Operation Performance Evaluation of Power Grid Enterprise Using a Hybrid BWM-TOPSIS Method

et al. 2017

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Electricity market reform is in progress in China, and the operational performance of power grid enterprises are vital for its healthy and sustainable development in the current electricity market environment. In this paper, a hybrid multi-criteria decision-making (MCDM) framework for operational performance evaluation of a power grid enterprise is proposed from the perspective of sustainability. The latest MCDM method, namely the best-worst method (BWM) was employed to determine the weights of all criteria, and the technique for order preference by similarity to an ideal solution (TOPSIS) was applied to rank the operation performance of a power grid enterprise. The evaluation index system was built based on the concept of sustainability, which includes three criteria (namely economy, society, and environment) and seven sub-criteria. Four power grid enterprises were selected to perform the empirical analysis, and the results indicate that power grid enterprise A1 has the best operation performance. The proposed hybrid BWM-TOPSIS-based framework for operation performance evaluation of a power grid enterprise is effective and practical.

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Network security situation prediction based on combining associated entropy and deep recurrent neural network

Xin-cun

Wang

2020

Trans Emerging Tel Tech

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The existing network security situation prediction algorithm cannot deal with the subjective attitude deviation of multi-experts, and the traditional sequential machine learning model cannot deal with the problem of deviation accumulation in time period. In this paper, an algorithm of network security situation prediction combining entropy correlation and deep time series network model is proposed. First, the expert fuzzy evaluation index is constructed by trigonometric fuzzy function, and the modified weighted dempster-shafer (DS) evidence reasoning correction index is used, then the loss and possibility matrix features are created, and finally the information security is evaluated by deep time series network. The simulation experiments are carried out on MIT dataset. The experiments analyze whether the features can cope with multi-expert conflicts, and evaluate the accuracy, robustness, and time efficiency of the algorithm.The experimental results show that the algorithm proposed in this paper has stronger fuzzy evaluation ability, stronger ability to deal with conflict opinions among experts, more accurate prediction of network security situation in time sequence, and higher robustness, but the efficiency of the algorithm has been maintained.

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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

Cited by 62 publications

References 28 publications

Comprehensive Performance Evaluation of Electricity Grid Corporations Employing a Novel MCDM Model

Comprehensive Performance Evaluation of Electricity Grid Corporations Employing a Novel MCDM Model

Operation Performance Evaluation of Power Grid Enterprise Using a Hybrid BWM-TOPSIS Method

Network security situation prediction based on combining associated entropy and deep recurrent neural network

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