The invention relates to a
time series data cleaning method and
system. The method comprises the following steps: 1) collecting one piece of
original data, wherein the
original data comprises multiple pieces of original
time series data; 2) carrying out random sampling and
estimation on the original
time series data to obtain the multiple pieces of
estimation data, completing vacancy points generated by the random sampling, and obtaining multiple pieces of completion
estimation data; 3) classifying all completion estimation data according to sampling time points to obtain multiple groups of time classification data, and sorting all groups of time classification data according to the magnitude to obtain multiple groups of sorting arrays; 4)
processing each group of sorting array to obtain one piece of corresponding mean data, wherein multiple groups of sorting arrays correspond to multiple pieces of mean data, and the mean data forms a mean series; 5) outputting the mean series, wherein the mean series is data for clearing aberrant points and high-
frequency noise. Integrated data cleaning is used for
processing vacancy values, removing aberrant points and smoothening
noise data.