Adding Sliding Time Window Algorithm for Identification and Filling of Abnormal Room Temperature Data
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.
indoor temperaturesliding time window algorithmabnormal data identificationdata filling
国家科技期刊平台
NSTL
万方数据
