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Parking garage recommendation method based on feed-forward lstm model

A recommendation method, parking lot technology, applied in the direction of indicating each vacant space in the parking lot, neural learning method, biological neural network model, etc., can solve the problem of not considering the influence of drainage, achieve low sensitivity of parking prices, and ease traffic flow Effects of pressure and precision improvement

Active Publication Date: 2021-12-31
ZHEJIANG UNIV OF FINANCE & ECONOMICS
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  • Abstract
  • Description
  • Claims
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Problems solved by technology

At the same time, in such an operation, the impact of drainage on regional traffic and the efficiency of vehicles arriving at the drainage yard after receiving drainage are not considered.

Method used

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  • Parking garage recommendation method based on feed-forward lstm model
  • Parking garage recommendation method based on feed-forward lstm model
  • Parking garage recommendation method based on feed-forward lstm model

Examples

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Embodiment

[0047] This embodiment provides a parking garage recommendation method based on a feed-forward LSTM model, which is used to guide vehicles queuing up in a hospital and relieve traffic pressure in the surrounding area of ​​the hospital. In this example, there are two hospitals, and the road distance between these two hospitals is 2 kilometers. Because the parking spaces in the two hospitals seriously do not match the parking needs of the hospital, a large number of vehicles are stranded at the entrance of the hospital during the working hours of the hospital. queue phenomenon. The road conditions in the area around the hospital are complex, and the parking capacity of the surrounding parking lots is limited. Many parking lots are located in office buildings. The distribution of daily parking spaces is at the same peak as the distribution of hospital parking spaces. It is very difficult for vehicles waiting to enter the hospital to find the parking spaces by themselves. Therefor...

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Abstract

The invention relates to a parking garage recommendation method based on a feed-forward LSTM model. The present invention comprehensively considers the time it takes for the vehicle to go to the traffic hotspot area to the parking lot, the time it takes to find a parking space in the parking lot, and the time it takes to leave the parking lot. The present invention uses weather data when predicting the convenience index and traffic index of the parking lot. , which can effectively improve the prediction accuracy. The improvement of the prediction accuracy helps to improve the parking experience of the car owner, and makes it easier for the car owner to accept the recommendation scheme proposed by the present invention. The present invention can effectively alleviate the traffic pressure around the traffic hot spot area.

Description

technical field [0001] The present invention relates to a method for recommending parking lots around traffic hot spots, and more specifically, to a method for recommending parking lots based on a feed-forward LSTM model. Background technique [0002] With the deepening of urbanization, the population and traffic of cities have far exceeded the scale that urban land and infrastructure can bear. Accelerate the construction of urban transportation infrastructure (road transportation system, subway rail transportation system, station and parking lot system, etc.), focus on improving the efficiency of the use of existing transportation facilities and equipment, etc. Traditional measures are limited by factors such as land resources, funds, and systems. It has entered the stage of development with diminishing marginal benefits, and the city's traffic capacity cannot be greatly increased in a short period of time. Especially in key traffic hotspot areas such as hospitals, it is i...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G08G1/01G08G1/14G06N3/04G06N3/08
CPCG08G1/0129G08G1/14G06N3/08G06N3/045
Inventor 武鑫张超张帅王高翔李桦媛
Owner ZHEJIANG UNIV OF FINANCE & ECONOMICS
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