煤气与热力2024，Vol.44Issue(8)：17-23,7.
加入滑动时间窗算法室温异常数据识别与填补
Adding Sliding Time Window Algorithm for Identification and Filling of Abnormal Room Temperature Data
摘要
Abstract
It is proposed to add sliding time window algorithm based on the method for identifying abnormal room temperature data.Combined with exam-ples,the optimal sliding parameters(sliding window width and sliding step size)and room temperature data acquisition interval were screened to verify the credibil-ity of the KNN algorithm in filling the excluded data.Adding the sliding time window algorithm can improve the accuracy of 3σ criterion,quartile method,and K-means clustering in identifying abnormal room tempera-ture data.The sliding window width,sliding step size,and room temperature data acquisition interval all have an impact on the accuracy of identifying abnormal room temperature data,and should be reasonably deter-mined.The credibility of the data filled by the KNN algorithm is relatively high,especially the proportion of excluded data is relatively small.关键词
室内温度/滑动时间窗算法/异常数据识别/数据填补Key words
indoor temperature/sliding time window algorithm/abnormal data identification/data filling分类
建筑与水利引用本文复制引用
张珂,曹姗姗,孙春华,夏国强,吴向东..加入滑动时间窗算法室温异常数据识别与填补[J].煤气与热力,2024,44(8):17-23,7.基金项目
国家重点研发计划"基于可再生能源热泵利用的复合型区域供热供冷系统关键技术研究与示范"(02021YFE0116100) （02021YFE0116100）
