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An Optimization Method of Overspeed Discrimination Model Based on bp Neural Network

A technology of BP neural network and optimization method, which is applied in the field of overspeed discrimination model optimization based on BP neural network, can solve problems such as errors, and achieve the effect of reducing errors and improving discrimination accuracy

Active Publication Date: 2020-08-11
HUAIYIN INSTITUTE OF TECHNOLOGY
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  • Application Information

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Problems solved by technology

[0004] In the study of overspeed identification, the overspeed identification model using the reverse deduction method has the characteristics of simplicity and convenience, but the meaning of individual factors in the model is different from that in the actual accident, resulting in errors, so that the identification accuracy of the overspeed identification model is still greatly improved space

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  • An Optimization Method of Overspeed Discrimination Model Based on bp Neural Network
  • An Optimization Method of Overspeed Discrimination Model Based on bp Neural Network
  • An Optimization Method of Overspeed Discrimination Model Based on bp Neural Network

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Embodiment Construction

[0044] The technical solution will be described in detail below through a preferred embodiment and in conjunction with the accompanying drawings.

[0045] (1) Determine the speeding discrimination model to be optimized. In this embodiment, the large vehicle speeding discrimination model of the vertical side-impact electric bicycle is the speeding discrimination model to be optimized.

[0046] The model to be optimized is as follows:

[0047]

[0048] In the formula, v 0 is the braking moment velocity, is the adhesion coefficient of the road surface, g is the acceleration of gravity, d is the braking distance before the collision of a large vehicle, L 1 is the braking distance of a large vehicle after collision, M is the mass of a large vehicle, m 1 is the rider mass, s 1 is the throw distance of the cyclist, H 1 is the height of the center of gravity of the cyclist, m 2 is the electric bicycle mass, s 2 is the throwing distance of the electric bicycle, H 2 is the t...

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Abstract

The invention discloses a method for optimizing an overspeed discrimination model based on a BP neural network. A correction coefficient is added to the error source factor of the model to be optimized, a simulation sample is collected, and the correction coefficient of the sample is calculated, and then the overspeed discrimination is finally realized through the neural network model. . The invention uses BP neural network to significantly reduce the error between the model output value and the standard value, and improves the discrimination accuracy of the overspeed discrimination model; the survey data of the accident scene can be input into the model to distinguish whether the speed is over, which solves the problem of traditional simulation software analysis accidents, It is convenient and accurate to identify the problem of overspeed that takes a long time; the overspeed identification model can be directly used in actual accident analysis.

Description

technical field [0001] The invention relates to the technical field of overspeed discrimination, in particular to an overspeed discrimination model optimization method based on BP neural network. Background technique [0002] With the development of my country's transportation and the continuous improvement of road grades, the degree of freedom of vehicle driving has also increased. And the driver will therefore relax his vigilance and increase the speed, causing traffic safety hazards. [0003] At present, speeding of motor vehicles has become the primary factor threatening traffic safety. Therefore, the research on motor vehicle overspeed identification is particularly important. [0004] In the study of overspeed identification, the overspeed identification model using the reverse deduction method has the characteristics of simplicity and convenience, but the meaning of individual factors in the model is different from that in the actual accident, resulting in errors, s...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q50/30G06N3/04G06N3/08G08G1/054
CPCG06N3/084G06Q10/04G08G1/054G06N3/045G06Q50/40
Inventor 包旭陈锦文周君李耘常绿夏晶晶陈大山朱胜雪
Owner HUAIYIN INSTITUTE OF TECHNOLOGY