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Method and system for short-term traffic flow prediction on urban roads

A traffic flow and short-term technology, which is applied in the traffic control system of road vehicles, traffic flow detection, traffic control system, etc., can solve the problems of LSSVM algorithm complexity, difficult parameters, and slow iterative convergence speed, so as to alleviate urban congestion, Effects of improved prediction accuracy and shortened calculation processing time

Active Publication Date: 2021-06-18
CETC BIGDATA RES INST CO LTD
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  • Application Information

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Problems solved by technology

However, the above optimized LSSVM algorithm is more complex, iterative convergence speed is slow, and the parameters are difficult to achieve the global optimal

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  • Method and system for short-term traffic flow prediction on urban roads
  • Method and system for short-term traffic flow prediction on urban roads
  • Method and system for short-term traffic flow prediction on urban roads

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Embodiment Construction

[0035] The present invention will be further described in detail below with reference to the accompanying drawings and examples to make the objects, technical solutions and advantages of the present invention. It will be appreciated that the specific embodiments described herein are intended to explain the present invention and is not intended to limit the invention.

[0036] figure 1 A method for predicting short-term traffic flow rate for urban roads in accordance with an embodiment of the present invention is shown. The method of this embodiment includes the following steps:

[0037]Step 101: Data Pretreatment

[0038] Specifically, for the selection of historical traffic flow data, the weather influencing factors is different, the value is different, and the data normalization process is unified to prevent the characteristic factor. The pre-treatment formula is as follows:

[0039]

[0040] Where: X 'is normalized; X is the original sample value; X max Represents the maximu...

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Abstract

The invention discloses a method and system for predicting short-term traffic flow on urban roads. The method specifically includes: data preprocessing; selecting the LSSVM kernel function; setting the solution problem dimension d, the maximum number of iterations Mit, "students" group n and other parameters; sorting the upper and lower generations of "students" optimally according to their fitness values; " and "Learning" stage learning; if the maximum number of iterations Mit is reached, and the prediction error condition is satisfied, according to the optimal "student" subject score, set the penalty parameter c and the kernel width parameter σ of LSSVM, and build a prediction model based on LSSVM to predict the city Predict the short-term traffic flow of the road; perform denormalized output; perform performance evaluation based on the prediction evaluation index.

Description

Technical field [0001] The present invention relates to the field of intelligent traffic system vehicle flow prediction techniques, and more particularly to methods and systems for short-term traffic flow rate predictions in urban roads. Background technique [0002] As the economy continues to develop rapidly, the number of urban car insurance has been innovative, and the urban traffic congestion has become a global challenge that plagues human life. Utty traffic induction and traffic control methods are used to alleviate traffic pressure, and as one of the core contents of the modern intelligent transportation system, accurate traffic flow forecast is the basis and key to solve traffic congestion and build smart urban traffic management systems. [0003] Traditional short-term traffic flow prediction methods have time series, self-return model, gray theory, etc. Such methods techniques are relatively mature and the structure is simple, but basically in linear rules, difficult t...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G08G1/01
CPCG08G1/0112G08G1/0125G08G1/0129G08G1/0145
Inventor 张鹏翔曹扬洒科进
Owner CETC BIGDATA RES INST CO LTD