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Continuous-time motor vehicle tail gas concentration predicting method for target road segments

A technology for predicting exhaust gas concentration and time, applied in prediction, neural learning methods, instruments, etc., can solve problems such as unsatisfactory prediction results, improve prediction accuracy and efficiency, ensure accuracy and credibility, and ensure completeness and effect of adequacy

Active Publication Date: 2018-06-08
安徽优思天成智能科技有限公司
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Problems solved by technology

[0004] However, the existing pollutant concentration prediction methods only start from the perspective of the pollutant itself, subjectively select possible influencing factors for physical modeling, and the prediction effect is not ideal

Method used

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  • Continuous-time motor vehicle tail gas concentration predicting method for target road segments
  • Continuous-time motor vehicle tail gas concentration predicting method for target road segments
  • Continuous-time motor vehicle tail gas concentration predicting method for target road segments

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Embodiment Construction

[0056] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0057] Such as figure 1 As shown, the present invention provides a method for predicting the continuous time of motor vehicle exhaust concentration at the target road section, specifically comprising the following steps:

[0058] Step S1, collecting motor vehicle exhaust concentration data within a specified period near the target road section in the city.

[0059] Wherein, the collection method of motor vehicle exhaust concentration data in step S1 specifically i...

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Abstract

The invention discloses a continuous-time motor vehicle tail gas concentration predicting method for target road segments. According to the method, an eRCNN (Region-based Convolutional Neural Network)model is constructed; a matrix containing continuous space-time tail gas concentration data of the road segments serves as the input of a network; the complex interactivity of the tail gas concentration among nearby road segments is naturally captured by using a convolution layer with no need for detailed characterization; in the meantime, an error feedback circulation layer is introduced to sense prediction errors caused by sudden changes of pollutant concentration; in addition, relationships among historical observation data are utilized and integrated to a great extent to improve the predicting accuracy and efficiency; and the method has a strong generalization ability and a certain social value and practical significance at the same time.

Description

technical field [0001] The invention belongs to the technical field of environmental monitoring, and relates to a method for predicting the concentration of motor vehicle exhaust, in particular to a continuous time prediction method for the concentration of motor vehicle exhaust aimed at a target road section. Background technique [0002] With social development and urban progress, in recent years, the number of motor vehicles in urban areas has continued to increase, and many social problems have emerged, such as serious urban traffic congestion, increased traffic accidents, motor vehicle exhaust pollution, drunk driving, etc. In big cities such as Beijing, Shanghai, and Guangzhou, motor vehicles have become the largest source of pollutants such as carbon monoxide, nitrogen oxides, and hydrocarbons. Since the emission of automobile exhaust gas is mainly between 0.3m and 2m, which happens to be within the breathing range of the human body, the health damage to the human bod...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/26G06N3/04G06N3/08
CPCG06N3/084G06Q10/04G06Q50/26G06N3/044G06N3/045
Inventor 杨钰潇李泽瑞杜晓冬吕文君
Owner 安徽优思天成智能科技有限公司
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