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
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