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Short-term traffic volume prediction method based on improved grey wolf algorithm

A forecasting method and technology of traffic volume, applied in traffic flow detection, traffic control system of road vehicles, forecasting, etc., can solve problems such as overcrowding, waste of time in public safety, etc., achieve good stability, meet accuracy and real-time performance, The effect of high prediction accuracy

Inactive Publication Date: 2020-10-13
NANTONG UNIVERSITY
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Problems solved by technology

One of the most serious problems is overcrowding, which poses public safety and time-wasting risks, and one of the ways to solve traffic congestion is to develop intelligent transportation systems

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  • Short-term traffic volume prediction method based on improved grey wolf algorithm
  • Short-term traffic volume prediction method based on improved grey wolf algorithm
  • Short-term traffic volume prediction method based on improved grey wolf algorithm

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specific Embodiment 1

[0046] The development platform and tools of the embodiment in the present invention are as follows:

[0047] Language: Python;

[0048] Tool libraries: NumPy, Pandas, TensorFlow GPU, Scikit Learn.

[0049] The data sources of this embodiment are as follows:

[0050] The present invention collects traffic flow data at intersections for a total of 63 days from July 20, 2018 to September 21, 2018, on a street in a certain city. The original data is stored in Oracle, with a total of about 12 million data. The original data includes 10 fields including passing time, intersection number, detection section number, lane number, vehicle type, vehicle speed, occupancy time, detector type (radar, video), area number, and lane direction type.

[0051] In the described embodiment, comprise the following steps:

[0052] Step 1) Import intersection data into Oracle database from urban intersection database, carry out data preprocessing to the intersection data stored in by NumPy, Pandas; ...

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Abstract

The invention discloses a short-time traffic volume prediction method based on an improved grey wolf algorithm. The method comprises the following steps: importing intersection data into an Oracle database from an urban intersection database, and carrying out the data preprocessing of the stored intersection data through NumPy and Pands; converting the data after data preprocessing into features and labels required by a supervised learning model; carrying out data standardization processing on the processed data by using deviation standardization; constructing a short-time traffic volume prediction model of the intersection based on a GRU neural network, inputting the standardized data into the model for training, and achieving the prediction of the traffic volume of the intersection at acertain moment in the future; and performing model optimization on the short-time traffic volume prediction model based on the improved grey wolf algorithm so that precision and stability can be enhanced. The method has the operation process of screening and selecting the intersection data, and by screening and selecting the intersection data, the accuracy of predicting the intersection traffic flow can be effectively improved.

Description

technical field [0001] The invention belongs to the technical field of short-term traffic volume forecasting, in particular to a short-term traffic volume forecasting method based on an improved gray wolf algorithm. Background technique [0002] In recent years, with the development of trade circles in big cities, traffic problems have gradually increased. One of the most serious problems is overcrowding, which poses public safety and time-wasting hazards, and one of the ways to solve traffic congestion is to develop intelligent transportation systems. [0003] The Intelligent Transportation System (ITS) is currently at the forefront of the world's transportation field, and has become one of the key points for all countries in the world to invest in capital advancement. Many advanced countries such as the United States, Japan and the European Union pay special attention to ITS, which is considered to be one of the effective means to improve traffic reliability, safety and r...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/01G08G1/081G06Q10/04G06Q50/26G06N3/00G06N3/04G06N3/08
CPCG08G1/0104G08G1/081G06Q10/04G06Q50/26G06N3/006G06N3/08G06N3/045
Inventor 施佺戴俊明曹阳沈琴琴苏永杰李赟波
Owner NANTONG UNIVERSITY