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文章摘要
一种多参量决策的非侵入式负荷辨识算法评价模型
Non-intrusive Load identification algorithm evaluation model based on the decision of multi-variable feature
Received:May 06, 2019  Revised:May 06, 2019
DOI:10.19753/j.issn1001-1390.2020.15.005
中文关键词: 非侵入式  层次分析  负荷辨识  性能评价
英文关键词: non-intrusive, analytic  hierarchy process, Load  identification, Comprehensive  Evaluation
基金项目:南方电网公司科技项目(ZBKJXM20170079)
Author NameAffiliationE-mail
Xiao yong Electrical Power Research Institute,Guangdong Guangzhou
china 
565788946@qq.com 
Wang Yaqian* Wuhan University,Hubei Wuhan 13006161303@163.com 
He Hengjing Electrical Power Research Institute,Guangdong Guangzhou 443943052@qq.com 
Zhou Dongguo Wuhan University,Hubei Wuhan dongguozhou@gmail.com 
Hu Wenshan Wuhan University,Hubei Wuhan wenshan.hu@whu.edu.cn 
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中文摘要:
      随着非侵入式负荷监测技术的广泛研究,然而负荷辨识算法的性能通常以准确率等单一因素进行评价,导致算法性能评价不合理。为此提出一种基于多参量决策的算法综合评价方法。该方法依据现有的算法评价的各项指标为基础,采用递阶层次结构模型构建非侵入式负荷辨识算法评价体系,然后采用各层次之间不同影响因素的权重比例方法,确定判别矩阵并进行一致性检验,最后根据归一化计算得到算法性能评价值,实现算法性能的有效评价。实验结果表明文中所提评价指标体系和综合算法评价模型能够有效评价算法性能,为后续推广应用奠定基础。
英文摘要:
      With the extensive research of non-intrusive load monitoring technology, the performance of the load identification algorithm is usually evaluated by a single factor such as accuracy, which leads to unreasonable performance evaluation. Thus, a comprehensive evaluation method based on multi-parameter decision making is proposed. Based on the indicators of the existing algorithm evaluation. The method constructs the non-intrusive load identification algorithm evaluation system by using the hierarchical structure model. Then, the weight ratio method of different influencing factors between different levels is used to determine the discriminant matrix and carry out the discriminant matrix. Consistency test, finally, the performance evaluation value of the algorithm is obtained according to the normalized calculation, and the performance of the algorithm is effectively evaluated. The experimental results show that the evaluation index system and the comprehensive algorithm evaluation model proposed in the paper can effectively evaluate the performance of the algorithm and lay a foundation for subsequent promotion and application.
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