Information system resource capacity prediction method based on AI algorithm

A technology of information system and forecasting method, applied in the direction of calculation, calculation model, error detection/correction, etc., can solve problems such as strong dependence on experts, extensive management, long planning cycle, etc., to achieve short planning cycle, convenient management, and resources. Effective use of the effect

Pending Publication Date: 2021-07-23
STATE GRID INFORMATION & TELECOMM BRANCH
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Current pain points: (1) Strong dependence on experts; (2) Serious w

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
  • Information system resource capacity prediction method based on AI algorithm
  • Information system resource capacity prediction method based on AI algorithm
  • Information system resource capacity prediction method based on AI algorithm

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0046] Next, the technical solutions in the embodiments of the present invention will be apparent from the embodiment of the present invention, and it is clearly described, and it is understood that the described embodiments are merely embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, there are all other embodiments obtained without making creative labor without making creative labor premises.

[0047] Refer to the attachment figure 1 Adherent Figure 4 , An information system resource capacity prediction method based on AI algorithm, including the following steps:

[0048] Step 1, extract sample data as needed and form a database;

[0049] Step 2, provide the AI ​​algorithm base by the Tensorflow machine learning framework, the Tsfresh timing data sign, the Scikit-Learn algorithm, and other computing frameworks;

[0050] Step 3, using the Holt-Winters timing calculation model and the linear regression + Gaussian nu...

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 discloses an information system resource capacity prediction method based on an AI algorithm. The method comprises the following steps: step 1, extracting sample data according to a required scene and forming a database; step 2, providing an AI algorithm basis through calculation frameworks such as a tensorflow machine learning framework, a tsfreh time sequence data feature library, a score-learning algorithm library and the like; step 3, adopting a Holt-winters time sequence calculation model and a linear regression + Gaussian accounting method to carry out machine learning training to obtain a prediction result; and step 4, comparing a predicted value with an actual value and carrying out visual display, the system directly predicts a relatively accurate result which can be used as a reference, resources are effectively utilized, the planning period is short, the management is convenient, the effect is ideal, and the predicted result can effectively guide customers.

Description

technical field [0001] The invention relates to the field of capacity prediction, in particular to an information system resource capacity prediction method based on an AI algorithm. Background technique [0002] Capacity prediction is to predict the capacity trend in the future time period through the analysis of historical data and model training. The value of capacity prediction is to automatically predict the future trend of resources based on the historical status of resources to help customers plan in advance. It mainly provides the following values: Improve Operation and maintenance efficiency and prediction accuracy reduce labor costs and achieve the best return on investment; from passive expansion to active prediction, realize capacity demand trend perception, resource early warning and early procurement; greatly shorten the resource planning cycle and improve resource planning efficiency ; Refined and visualized resource capacity management, more accurate and intu...

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
IPC IPC(8): G06F11/34G06N20/00
CPCG06F11/3409G06F11/3452G06N20/00
Inventor 何云瑞闫祎颖李扬陈亮党义杰
Owner STATE GRID INFORMATION & TELECOMM BRANCH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products