Method for checking abnormity of time sequence conforming to approximately normal distribution
A technology of time series and normal distribution, applied in the field of anomaly detection, can solve the problems of large lag in data anomaly detection, lack of scientificity and rationality, etc., to increase scientificity and rationality, good reproducibility, and reduce requirements Effect
Inactive Publication Date: 2017-06-30
北京北青厚泽数据科技有限公司
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[0004] The present invention provides a method for checking the anomaly of time series that obeys approximately normal distribution, so as to solve the problems in the prior art that data anomaly detection has a large hysteresis and lacks scientificity and rationality
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[0017] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings, but the present invention can be implemented in many different ways defined and covered by the claims.
[0018] The present invention provides a method for checking the abnormality of the time series that obeys the approximate normal distribution, which is not only applicable to the outpatient volume, hospitalization volume, and operation volume of the hospital, but also to the transaction volume, transaction volume, and transportation field of the bank. Traffic volume, network traffic data, etc. Said method among the present invention comprises:
[0019] Step 1. Obtain historical data of key management indicators (take hospitals as an example, such as outpatient volume, hospitalization volume, operation volume, etc.) arranged in chronological order;
[0020] Step 2, generating a normal probability diagram of the key management index; the normal proba...
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The invention provides a method for checking the abnormity of a time sequence conforming to the approximately normal distribution. The method comprises the following steps: 1, acquiring historical data, which are arrayed according to the time sequence, of key management indicators; 2, generating a normal probability graph of the key management indicators; 3, judging whether the data of the key management indicators have latent abnormal values or not according to the normal probability graph, and if YES, entering step 4; 4, checking whether an abnormal value exists or not in the time sequence according to generalized ESD (electro-static discharge) statistics. According to the method provided by the invention, an abnormal mode can be scientifically defined, and automatic detection for the abnormal mode and timely discovery of the abnormity are realized; a manager does not need to have certain management experience, so that the requirement for the manager is reduced; the method is high in replicability, and the scientificity and the reasonability of forecasting are improved.
Description
technical field [0001] The invention relates to the field of anomaly detection, in particular to a method for inspecting anomalies of time series that obey approximately normal distribution. Background technique [0002] With the continuous improvement and improvement of hospital informatization, hospitals have generated a large amount of data, which has the characteristics of high value and large dimension. It is precisely because of the high complexity of the data that it is difficult to find when some indicators of the hospital are abnormal, and the abnormal detection of some important indicators has an important impact on hospital management decision-making. Therefore, how to timely and effectively detect the abnormal pattern of key indicators of hospital management and ensure the normal operation of the hospital is of great significance. The abnormality of key indicators of hospital management refers to the situation that the key indicators of hospital management devia...
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IPC IPC(8): G06F19/00
CPCG16H40/20
Inventor 夏一粟刘红跃
Owner 北京北青厚泽数据科技有限公司