基于粒子群优化最小二乘支持向量机的火电厂清洁生产综合评价

Wei Sun, Yi Liang
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引用次数: 3

摘要

火电厂清洁生产是指在发电过程中始终如一地实施全面预防的环境战略,这对提高火电厂的竞争力,实现可持续发展将起到重要作用。在调查分析国内外清洁生产研究概况的基础上,根据火电厂清洁生产的特点构建了火电厂清洁生产评价指标体系。本文提出用最小二乘支持向量机算法结合粒子群优化算法确定最优参数组合,实现清洁生产综合评价模型。通过对5家电厂清洁生产进行综合评价,并与传统的最小二乘支持向量机方法进行比较,发现平均相对误差小于0.285%,验证了该模型在评价清洁生产时的有效性和效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comprehensive Evaluation of Cleaner Production in Thermal Power Plants Using Particle Swarm Optimization Based Least Squares Support Vector Machines
Thermal power plant cleaner production means to consistently apply the overall prevention environmental strategy to electricity production process, which will play a significant role in enhancing the competitiveness of the thermal power plants and achieving sustainable development. On the basis of investigation and analysis of domestic and foreign research profile on cleaner production, according to the characteristics of the thermal power plants cleaner production we construct power plants clean production evaluation index system. In this paper, we put forward the least squares support vector machine algorithm with particle swarm optimization algorithm to determine the optimal parameter combination to achieve the comprehensive evaluation models of cleaner production. Through the comprehensive evaluation of five power plants cleaner production and its comparison with the traditional method of least squares support vector machine, we found that the average relative error is less than 0.285%, which verified the validity and effect of this model when evaluating cleaner production.
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