CAJ | 학술논문

　　研究模糊c-均值聚类算法在电力线路巡检中的应用。针对模糊c-均值聚类算法对孤立点数据比较敏感、实际应用中聚类数目通常都是未知的等不足，提出一种改进的模糊c-均值聚类算法对电力线路巡检中天气、地质、巡检线路等级、材料等突出的几项影响因素建立电力线路巡检模型，通过降低孤立点的影响，对聚类数目进行优选，采用改进的模糊c-均值聚类算法对所建立的模型进行仿真实验，仿真结果表明该模型是有效的。该算法应用在电力线路巡检中能更准确及时发现缺陷，利于及时处理问题。
　　연구모호c-균치취류산법재전력선로순검중적응용。침대모호c-균치취류산법대고립점수거비교민감、실제응용중취류수목통상도시미지적등불족，제출일충개진적모호c-균치취류산법대전력선로순검중천기、지질、순검선로등급、재료등돌출적궤항영향인소건립전력선로순검모형，통과강저고립점적영향，대취류수목진행우선，채용개진적모호c-균치취류산법대소건립적모형진행방진실험，방진결과표명해모형시유효적。해산법응용재전력선로순검중능경준학급시발현결함，리우급시처리문제。
The paper deals with the fuzzy c-means clustering algorithm in the application of the electric power line inspection. According to the shortage of the fuzzy c-means clustering algorithm is more sensitive to isolated point data, the practical application of clustering number is usually unknown, proposed an improved fuzzy c-means clustering algorithm for several outstanding influencing factors of the electric power line inspection, such as, weather, geology, inspection line level, material, to establish electric power line inspection model, by reducing the influence of the isolated point data, opti-mizing the clustering number, then the improved fuzzy c-means clustering algorithm was used to simulate, simulation re-sults show that the model is effective. The algorithm used in the electric power line inspection can be more accurate and timely found defects, be beneficial to deal with problems in time.