Performance Evaluation of Energy Transition Based on the Technique for Order Preference by a Similar to Ideal Solution and Support Vector Machine Optimized by an Improved Artificial Bee Colony Algorithm

Zhen Li, Yun Li and Yanbin Li
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Zhen Li: School of Economics and Management, North China Electric Power University, Beijing 102206, China
Yun Li: China National Institute of Standardization, Beijing 100191, China
Yanbin Li: School of Economics and Management, North China Electric Power University, Beijing 102206, China

Energies, 2019, vol. 12, issue 16, 1-21

Abstract: Energy transition is an important factor when dealing with climate change and energy crisis under resource constraints. The performance evaluation of it is significant for improving and promoting the process of energy transition. This paper explores the application of the support vector machine improved by the artificial bee colony algorithm (IABC-SVM) method in the energy transition performance evaluation process. It provides an intelligent evaluation tool for the evaluation of the regional energy transition performance. Firstly, the evaluation indicator system of energy transition is constructed from five dimensions: energy supply, demand, efficiency, institution, and environment. Then, the technique for order preference by a similar to ideal solution improved by a combination weighting (CW-TOPSIS) method and IABC-SVM are constructed. After that, according to the evaluation values of 30 provinces in China calculated by CW-TOPSIS, 10-fold cross validation is used to compare the errors of support vector machine (SVM), support vector machine optimized by the artificial bee colony algorithm (ABC-SVM), and IABC-SVM, which proves the effectiveness and accuracy of IABC-SVM in evaluating the performance of energy transition. Finally, the IABC-SVM is used to evaluate the energy transition performance of 30 provinces in 2016. Through a comparative analysis, the relevant suggestions of energy transition are put forward.

Keywords: energy transition; evaluation; the technique for order preference by a similar to ideal solution improved by combination weighting; support vector machine improved by the artificial bee colony algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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