Driving behavior evaluation method based on FCM clustering and BP neural network

A technology of BP neural network and clustering algorithm, which is applied in the field of posture behavior evaluation based on FCM clustering and BP neural network, can solve the problems of insufficient scientific and accurate evaluation results, and achieve the effect of improving accuracy and scientificity

Inactive Publication Date: 2017-09-12
中科美络科技股份有限公司
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The evaluation process is highly subjective, and the ev

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  • Driving behavior evaluation method based on FCM clustering and BP neural network
  • Driving behavior evaluation method based on FCM clustering and BP neural network
  • Driving behavior evaluation method based on FCM clustering and BP neural network

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[0042] In order to further illustrate the features of the present invention, please refer to the following detailed description and accompanying drawings of the present invention. The accompanying drawings are for reference and description only, and are not intended to limit the protection scope of the present invention.

[0043] Such as figure 1 As shown, the present embodiment discloses a driving behavior evaluation method based on FCM clustering and BP neural network, the method includes the following steps S1 to S6:

[0044] S1. Query the driving satellite positioning signal set of the sample vehicle from the Internet of Vehicles database as a sample data set;

[0045] S2. Extracting the driving behavior characteristic parameters of the sample vehicle from the sample data set;

[0046] S3. Build a Hadoop-based Spark cluster platform, and save the driving behavior characteristic parameters in the distributed file system HDFS;

[0047] It should be noted that building a H...

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Abstract

The invention discloses a driving behavior evaluation method based on FCM clustering and a BP neural network, belonging to the technical field of the Internet of vehicles. The method comprises the following steps: querying a driving satellite positioning signal set of a sample vehicle from an Internet-of-vehicles database as a sample data set; extracting the driving behavior characteristic parameters of the sample vehicle from the sample data set; building a cluster platform based on Spark of Hadoop to run an FCM clustering algorithm, and getting a clustering result of the driving behavior characteristic parameters according to the preset number of clusters; creating a BP neural network, normalizing the clustering result of the driving behavior characteristic parameters, and taking the normalized clustering result as a training sample to train the created BP neural network; and using the trained BP neural network to evaluate a normalized driving behavior to be evaluated. By mining and analyzing Internet-of-vehicles data, driving behavior evaluation is more accurate and scientific.

Description

technical field [0001] The invention relates to the technical field of the Internet of Vehicles, in particular to a posture behavior evaluation method based on FCM clustering and BP neural network. Background technique [0002] In recent years, with the rapid development of Internet of Things technology and the continuous popularization of Internet of Vehicles technology, Internet of Vehicles mobile devices such as vehicle terminals generate a large amount of Internet of Vehicles data all the time, and it is very convenient to use these devices to realize the monitoring, dispatching and monitoring of large-scale vehicles. Remote management, so as to improve the efficiency of vehicle use, and facilitate the management of government and enterprise vehicles. [0003] At present, the evaluation of driving speed behavior is generally through a series of driving behavior deduction units: rapid acceleration deduction unit, rapid deceleration deduction unit, sharp turn deduction uni...

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Application Information

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IPC IPC(8): G06Q10/06G06K9/62G06N3/08B60W40/09
CPCG06N3/084G06Q10/0639B60W40/09G06F18/23211
Inventor 吴仲城吴紫恒李芳张俊罗健飞
Owner 中科美络科技股份有限公司
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