关键词: 空调使用可靠性, 聚类算法, 元胞遗传算法, 模糊C-均值, 粒度评价

Abstract: Based on the analysis of factors which influenced the operational reliability of Air Conditioning (AC),aiming at the minimum difference of operational reliability of AC in similar regions,a multivariable high-dimensional clustering model of operational reliability on the basis of working environmental factors and user habit factors was established,and a dynamic optimal-selection cellular genetic clustering algorithm for solving the model was proposed.By introducing information entropy and optimal-selection-based strategy into canonical cellular genetic algorithm and fuzzy C-means,as well as using the new dynamic crossover and two-combination mutation operations,the algorithm integrated the merits of fuzzy C-means clustering method's fast convergence speed and cellular genetic algorithm's good diversity and strong capability of global search.Through testing six benchmark datasets,the proposed algorithm was proved to have better clustering accuracy and stability than FCM,GA-FCM,FCM-IDPSO.It was especially suitable for solving clustering problems of high dimensions.The proposed algorithm was applied to solve the model and evaluate the validity of granularity partition results,and then the optimal partition scheme was determined.It could effectively solve the relevant practical engineering problems.

Key words: operational reliability of air conditioning, clustering algorithm, cellular genetic algorithm, fuzzy C-means, granularity evaluating