Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Method and system for predicting trend of monitoring data based on deep learning

A monitoring data and deep learning technology, applied in data processing applications, electrical digital data processing, special data processing applications, etc., can solve problems such as obvious fluctuating sawtooth, false alarm interference, and increasing the monitoring cycle

Inactive Publication Date: 2018-03-23
MICRO DREAM TECHTRONIC NETWORK TECH CHINACO
View PDF2 Cites 11 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Another problem is that the results brought about by the moving average operation, such as obvious fluctuating sawtooth, are likely to cause false alarms and interference, and the monitoring cycle should be increased

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method and system for predicting trend of monitoring data based on deep learning
  • Method and system for predicting trend of monitoring data based on deep learning
  • Method and system for predicting trend of monitoring data based on deep learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0026] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0027] Such as figure 1 As shown, as an embodiment, the method for predicting monitoring data trends based on deep learning provided by the present invention includes:

[0028] 101. The offline training system extracts some data from real-time streaming data to form a data set, and calculates the data set to obtain a prediction model;

[0029] 102. The real-time online system extracts some data from the real-time streaming data to form a forecast set, and use...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to the technical field of computer monitoring, and in particular relates to a method and system for predicting the trend of monitoring data based on deep learning. The method includes the steps in which, an offline training system extracts a plurality of data from real-time streaming data to form a data set, and calculating the data set to obtain a prediction model; and a real-time online system extracts a plurality of data from the real-time streaming data to form a prediction set, and calculating the prediction set by using the prediction model to obtain a prediction result of the future streaming data of a monitoring system, wherein, the intersection of the data set and the prediction set is empty. In the invention, the offline training system obtains the prediction model by analyzing the real-time streaming data, and then the real-time online system combines the prediction model with the real-time streaming data to obtain the prediction result of the future streaming data of the monitoring system. The result can serve as a good reference for future trends in monitoring data, and a great deal of efforts and time can be saved for operation and maintenance personnel.

Description

technical field [0001] The invention relates to the technical field of computer monitoring, in particular to a method and system for predicting monitoring data trends based on deep learning. Background technique [0002] The existing operation and maintenance monitoring system is visualized through the time series of statistical historical data, so that the operation and maintenance personnel can clearly see the fluctuation of indicators and analyze the results. When the displayed value reaches or exceeds the specified value, we believe that the monitored An exception occurred in the system. However, the current method only displays the historical data, and does not involve the mining of the laws of the data itself and the analysis of future trends. [0003] The business indicator data of daily operation and maintenance will have some obvious abnormalities compared with yesterday, obvious problems of continuous deviation, and indicator data drifting over time. In the past,...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06F17/30
CPCG06Q10/06375G06F16/182G06F16/254
Inventor 方皓达彭冬黄帅
Owner MICRO DREAM TECHTRONIC NETWORK TECH CHINACO
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com