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Prediction model training method, data monitoring method and device, equipment and medium

A data monitoring method and prediction model technology, applied in the field of devices, data monitoring methods, equipment and media, and prediction model training methods, can solve the problems of low accuracy of data prediction results, achieve strong timing, improve accuracy and efficiency fast effect

Inactive Publication Date: 2018-02-23
PING AN TECH (SHENZHEN) CO LTD
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Embodiments of the present invention provide a prediction model training method, data monitoring method, device, equipment, and media to solve the problem of low accuracy of current data prediction results

Method used

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  • Prediction model training method, data monitoring method and device, equipment and medium
  • Prediction model training method, data monitoring method and device, equipment and medium
  • Prediction model training method, data monitoring method and device, equipment and medium

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Experimental program
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Embodiment 1

[0038] figure 1 A flow chart of the prediction model training method in this embodiment is shown. The predictive model training method is applied to terminal devices configured by financial institutions such as banks, securities, and insurance, or other institutions, and is used to conduct predictive model training using business data generated by financial institutions or other institutions, so as to predict the future based on the trained predictive model. Business data is predicted to achieve the purpose of artificial intelligence monitoring. Such as figure 1 As shown, the prediction model training method includes the following steps:

[0039] S110: time-mark the original service data and divide it according to a preset time limit, and obtain training service data carrying a time-series state.

[0040] Among them, the original business data is the business data formed in the production and operation process of the financial institution or other institutions. The busines...

Embodiment 2

[0069] Figure 4 A functional block diagram of a predictive model training device corresponding to the predictive model training method in Embodiment 1 is shown. Such as Figure 4 As shown, the prediction model training device includes a training service data acquisition module 110 , a data division module 120 , an original prediction model acquisition module 130 and a target prediction model acquisition module 140 . Wherein, the implementation functions of the training business data acquisition module 110, the data division module 120, the original prediction model acquisition module 130 and the target prediction model acquisition module 140 correspond to the corresponding steps of the prediction model training method in Embodiment 1, in order to avoid repeating, This embodiment does not describe in detail one by one.

[0070] The training service data acquisition module 110 is configured to time stamp the original service data and divide it according to a preset time limit...

Embodiment 3

[0082] Figure 5 The data monitoring method in this embodiment is shown. This data monitoring method can be applied to terminal equipment configured by financial institutions such as banks, securities, insurance, or other institutions that need data monitoring, so as to monitor future business data based on collected original business data and make timely adjustment strategies. As shown in Figure N, the data monitoring method includes the following steps:

[0083] S210: Obtain a data monitoring instruction, where the data monitoring instruction includes a current time, a preset time limit, and a monitoring index.

[0084] Wherein, the data monitoring instruction refers to an instruction for controlling the terminal device to perform service data monitoring. The current time is the system time of the terminal device, and the current time is a specific system day. The monitoring index refers to the category of service data to be monitored, and the monitoring index may corresp...

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Abstract

The invention discloses a prediction model training method, a data monitoring method and device, equipment and a medium. The prediction model training method comprises the steps that time-stamping iscarried out on original service data, and the data are divided according to a preset deadline to acquire training service data carrying a time sequence state; the training service data are divided into a training set and a test set according to a preset ratio; a training set is used to train a long short term memory cycle neural network model to acquire an original prediction model; and the testset is used to test the original prediction model to acquire a target prediction model. The prediction model training method has the advantages of high time sequence and high accuracy in predicting.

Description

technical field [0001] The present invention relates to the field of data monitoring, in particular to a prediction model training method, data monitoring method, device, equipment and medium. Background technique [0002] With the development of the market economy, the competition among enterprises is becoming more and more fierce. In order to improve the competitiveness of enterprises, enterprises conduct big data analysis on historical business data to predict future business development trends and make strategic adjustments. Currently, the SVM (Support Vector Machine, Support Vector Machine) model is used for big data analysis of historical business data. This method lacks consideration of the autocorrelation of its own data and does not have the ability to predict time series data, making the data prediction results accurate. The rate is lower. Contents of the invention [0003] Embodiments of the present invention provide a prediction model training method, data mon...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06Q30/02G06Q40/00G06K9/62G06N3/04G06N3/08
CPCG06N3/049G06N3/084G06Q10/0637G06Q30/0202G06Q40/00G06F18/214G06F18/24
Inventor 张川顾青山金鑫温善安李磊王定鑫李泳章
Owner PING AN TECH (SHENZHEN) CO LTD
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