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Description: Sustainability, Vol. 10, Pages 231: Sustainability Evaluation of Power Grid Construction Projects Using Improved TOPSIS and Least Square Support Vector Machine with Modified Fly Optimization Algorithm Sustainability doi: 10.3390/su10010231 Authors: Dongxiao Niu Yan Li Shuyu Dai Hui Kang Zhenyu Xue Xianing Jin Yi Song The electric power industry is of great significance in promoting social and economic development and improving people’s living standards. Power grid construction is a necessary part of infrastructure construction, whose sustainability plays an important role in economic development, environmental protection and social progress. In order to effectively evaluate the sustainability of power grid construction projects, in this paper, we first identified 17 criteria from four dimensions including economy, technology, society and environment to establish the evaluation criteria system. After that, the grey incidence analysis was used to modify the traditional Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), which made it possible to evaluate the sustainability of electric power construction projects based on visual angle of similarity and nearness. Then, in order to simplify the procedure of experts scoring and computation, on the basis of evaluation results of the improved TOPSIS, the model using Modified Fly Optimization Algorithm (MFOA) to optimize the Least Square Support Vector Machine (LSSVM) was established. Finally, a numerical example was given to demonstrate the effectiveness of the proposed model.

Description: Sustainability, Vol. 10, Pages 860: Comprehensive Evaluation for Operating Efficiency of Electricity Retail Companies Based on the Improved TOPSIS Method and LSSVM Optimized by Modified Ant Colony Algorithm from the View of Sustainable Development Sustainability doi: 10.3390/su10030860 Authors: Dongxiao Niu Si Li Shuyu Dai The electricity market of China is currently in the process of a new institutional reform. Diversified electricity retail entities are gradually being established with the opening of the marketing electricity side. In the face of a complex market environment and fierce competition, the operating efficiency can directly reflect the current market position and development of electricity retail companies. TOPSIS method can make full use of the information of original data, calculate the distance between evaluated objects and the ideal solutions and get the relative proximity, which is generally used in the overall department and comprehensive evaluation of the benefits. Least squares support vector machine (LSSVM), with high convergence precision, helps save the training time of algorithm by solving linear equations and is used to predict the comprehensive evaluation value. Considering the ultimate goal of sustainable development, a comprehensive evaluation model on operating efficiency of electricity retail companies based on the improved TOPSIS method and LSSVM optimized by modified ant colony algorithm is proposed in this paper. Firstly, from the view of sustainable development, an operating efficiency evaluation indicator system is constructed. Secondly, the entropy weight method is applied to empower the indicators objectively. After that, based on the improved TOPSIS method, the reverse problem in the evaluation process is eliminated. According to the relative proximity between the evaluated objects and the absolute ideal solutions, the scores of comprehensive evaluation for operating efficiency can then be ranked. Finally, the LSSVM optimized by modified ant colony algorithm is introduced to realize the simplified expert scoring process and fast calculation in the comprehensive evaluation process, and its improved learning and generalization ability can be used in the comprehensive evaluation of similar projects. The example analysis proves that the comprehensive evaluation model proposed in this paper can provide scientific and effective evaluation results of the operating efficiency of electricity retail companies.