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

Intelligent traffic predicting method

A technology of traffic prediction and traffic, which is applied in the direction of monitoring/monitoring/test arrangement, electrical components, selection devices, etc., can solve problems such as difficult to predict traffic during holidays, and achieve improved traffic prediction accuracy and high traffic prediction accuracy , Overcoming the effect of large traffic fluctuations

Inactive Publication Date: 2007-10-10
杨苹
View PDF0 Cites 18 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] Aiming at the problem that the general traffic forecasting method has large traffic fluctuations and is significantly affected by holidays, the traffic forecasting accuracy of mobile communication networks is not high. An intelligent traffic forecasting method that solves the problem of unpredictable traffic during holidays

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
  • Intelligent traffic predicting method
  • Intelligent traffic predicting method
  • Intelligent traffic predicting method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0058] As shown in FIG. 1 , it is a schematic diagram of traffic decomposition in the steady period of the intelligent traffic forecasting method of the present invention. First divide the historical traffic data of the last three years into N sections reasonably, and each section is approximated as a stationary random process, and then decompose the traffic in each stationary period according to Figure 1: the periodic component and the trend component are composed of two parts . In Figure 1, (a) is the traffic in the original stationary period, (b) is the traffic of the trend component (univariate linear regression model), and (c) is the traffic of the periodic component.

[0059] As shown in FIG. 2 , it is a schematic diagram of template matching of the intelligent traffic prediction method of the present invention. For each period of steady-state traffic, first train based on historical periodic component data to obtain a week’s traffic template curve, as shown in Figure 2...

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 method comprises: 1) taking out the data of recent years to make training in order to determine the initial parameter, growth factor, template value, and the template value of traffic on each holiday; 2) according to the inputted predication time length, estimating it is a short time or middle-long time traffic predication in stable period to select different stable traffic predication algorithm; 3) according to the result from step 2, based on different algorithm, predicating the traffic in stable period; 4) according to the parameter determined in step 1, each holiday length and type in the predicated time, using relevant holiday traffic predication algorithm to predicate the traffic in holiday; 5) according to the result from step 4 and step 5, making interface smooth process for the traffic in stable time and the traffic in holiday to synthesis predication traffic which is outputted to relevant device.

Description

technical field [0001] The invention relates to a traffic prediction algorithm, in particular to an intelligent prediction method for improving the accuracy of traffic prediction. Background technique [0002] Traffic forecasting is to understand the rules and characteristics of system traffic changes from the relevant historical records obtained, establish a mathematical model that can describe the characteristics of traffic changes, and then use it to predict under certain accuracy requirements. Traffic volume for a certain period of time in the future. [0003] Traffic prediction is divided into short-term, medium-term and long-term prediction according to the length of prediction. [0004] Short-term traffic forecast refers to the forecast a few days in advance, mainly used for preventive control and emergency handling needs, especially for holidays and sudden large-scale activities, and for real-time adjustment of network equipment, while ensuring communication quality...

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): H04M3/24H04Q3/00
Inventor 杨苹
Owner 杨苹
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