Computer data mining and clustering method based on time sequence

Abstract

The invention discloses a computer data mining and clustering method based on a time sequence. According to the computer data mining and clustering method, denoising and normalization processing is performed on input sample sets X and Y, and extreme point solving is performed on the processed time sequence so that extreme point sequences X' and Y' are obtained; then isometric processing is performed on X' and Y', and classification sequences X" and Y" with equal length are obtained after isometric processing; then class distance calculation is performed on the processed sequences X" and Y", the two classes of the maximum distance are combined and one class is reduced after combination; then class distance calculation is cyclically performed on the processed classification sequences X" and Y" and two classes of the maximum distance are combined until the number of clusters is equal to preset data and then clustering ends; and finally a clustering result is outputted. According to the method, the time sequence data of high data volume and high dimension can be effectively processed, the method is easy and practicable without depending on concrete sequences, data mining and clustering can be effectively performed, and mass data can be effectively compressed and the main characteristics of the data can be maintained.

Description

technical field [0001] The invention relates to the field of computer data mining technology, in particular to a time series-based computer data mining clustering method. Background technique [0002] With the continuous development of social informatization and the continuous expansion of information technology application fields, more and more data have been accumulated in various application fields, including economics, medical care, construction, and the environment. Since the 1980s, the total amount of data around the world has grown rapidly, even doubling in a few months. However, how to effectively use and analyze these data information and obtain hidden useful information from them has become a A huge challenge. Among these massive data, some data are arranged in time order, and this kind of data is called time series (TimeSeries). There are time series in various application fields. Through in-depth study of these time series, it is of great social significance an...

AI Technical Summary

Problems solved by technology

Most of the current methods may only show relatively good performance in one aspect, but cannot combine to have a good performance in other aspects.

Obviously, there are still some deficiencies in the past research on time series. For time series mining problems in different fields, traditional mining methods are no longer applicable, and some new technologies and methods need to be sought.

Images