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Motorcycle helmet wearing condition prediction and evaluation model based on neural network

A neural network and evaluation model technology, applied in the field of traffic safety, can solve problems such as personal safety accidents and inadequate protective measures, and achieve new effects in improving road traffic safety, ensuring people's lives and safety, and in the application field

Pending Publication Date: 2020-11-06
XI'AN PETROLEUM UNIVERSITY
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to propose a neural network-based prediction and evaluation model for wearing a motorcycle helmet in order to solve the problem that personal safety accidents are easily caused if the protection measures for motorcycle and electric bicycle owners are not in place.

Method used

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  • Motorcycle helmet wearing condition prediction and evaluation model based on neural network
  • Motorcycle helmet wearing condition prediction and evaluation model based on neural network
  • Motorcycle helmet wearing condition prediction and evaluation model based on neural network

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Embodiment Construction

[0037] 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.

[0038] see Figure 1-4 , the present invention provides a technical solution: a neural network-based motorcycle helmet wearing condition prediction and evaluation model, comprising:

[0039] S1. Preprocess the training sample data, then determine parameters such as input and output, hidden layer transfer function, and finally determine the network topology.

[0040] S2. Collect the initial BP neural network weights and thresholds, pass them to GA to encode the ini...

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Abstract

The invention discloses a motorcycle helmet wearing condition prediction and evaluation model based on a neural network. The invention belongs to the technical field of traffic safety. Training sampledata are preprocessed; parameters such as input and output, a hidden layer transfer function and the like are determined; and finally, a network topology structure is determined, an initial BP neuralnetwork weight and a threshold are collected, the initial BP neural network weight and the threshold are transmitted to a GA to encode the initial value to generate an initial population, then a fitness function is determined to calculate fitness, chromosomes with high fitness is selected to copy, and then crossing and mutating are carried out to generate a new population. In the present invention, a GA-BP neural network prediction model of motorcycle helmet wearing conditions is used; through cooperation with data collection, the helmet wearing condition of the driver can be predicted to score whether inclination of police force is needed or not; through prediction, a traffic police department can conveniently distribute police force to check and supervise the driver in a section where the phenomenon of not wearing helmets is serious, the road traffic safety is improved, the life safety of people is guaranteed, the application field is new, and the practical significance value is achieved.

Description

technical field [0001] The invention belongs to the technical field of traffic safety, and in particular relates to a neural network-based prediction and evaluation model for wearing a motorcycle helmet. Background technique [0002] Genetic Algorithm (GA) was first proposed by John Holland in the United States in the 1970s. This algorithm is designed and proposed according to the evolution law of organisms in nature. It is a calculation model of the biological evolution process that simulates the natural selection and genetic mechanism of Darwin's biological evolution theory. It is a search for the optimal solution by simulating the natural evolution process (according to the fitness function, select the one with high fitness each time it evolves, and eliminate the adaptive one. low individual) (that is, natural selection, survival of the fittest) method. The algorithm converts the problem-solving process into a process similar to the selection, crossover, and mutation of ...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/26G08G1/01G06N3/08G06N3/12
CPCG06Q10/04G06Q50/26G08G1/01G06N3/084G06N3/126
Inventor 李彤张奇志
Owner XI'AN PETROLEUM UNIVERSITY
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