Regional cluster analysis of Mainland China based on factors of the reliability of air-conditioning systems
Regional cluster analysis of Mainland China based on factors of the reliability of air-conditioning systems
复制标题
基于空调系统可靠性因素的中国大陆区域聚类分析
DOI：
10.1080/23744731.2016.1250561
复制
发表时间：
2017
影响因子：
1.9
通讯作者：
Sun Zheng
中科院分区：
文献类型：
--
作者：
Jie Li-Lin;Liu Wei-Dong;Qiu Li-Ping;Teng Sha-Sha;Sun Zheng
为了使空调系统在不同区域的使用可靠性差异最小化，提出了一种基于空调系统可靠性因素的区域聚类方法。本研究在分析调查影响空调系统可靠性的自然环境因素和用户习惯因素的区域差异的基础上，建立了区域聚类综合评价模型。设定空调制冷制热的判断标准，准确量化7个聚类指标。采用Ward法计算不同距离的权重系数。采用加权Ward聚类算法，分别从自然环境因素和用户习惯因素两个角度对区域进行聚类。将两种聚类结果综合起来，通过二次聚类分析得到最终结果。最后，以中国大陆31个省级行政区的区域聚类为例，验证了本文方法的适用性和有效性。研究结果可为准确预测不同地区空调系统的使用可靠性奠定基础。对冰箱、洗衣机、热水器、太阳能路灯等的类似研究也有很好的参考价值。
With an aim to minimize the difference of use reliability of air-conditioning systems in different regions, a clustering method for classifying regions based on factors of the reliability of air-conditioning systems is proposed. This study establishes a comprehensive evaluation model of regional clustering on the basis of analysis and investigation about the regional differences of natural environmental factors and user habit factors that influence the reliability of air-conditioning systems. A judging criterion of refrigeration and heating of air conditioners is set to accurately quantify seven clustering indicators. The Ward method is used to calculate weight coefficients of different distance. The weighted Ward clustering algorithm is used for clustering regions from the perspectives of natural environmental factors and user habit factors, respectively. Two kinds of clustering results are integrated together to obtain the final results by secondary clustering analysis. Finally, the regional clustering of 31 provincial administrative areas in mainland China is presented to verify the applicability and validity of the method proposed in this study. The results of this study might establish the foundation for accurately predicting the use reliability of air-conditioning systems in different regions. It also provides good reference value for the similar study of refrigerators, washing machines, water heaters, solar street lamps, etc.