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BP neural network based on PCA and hazardous chemicals Vehicle Identification

Author: WangZhanKui
Tutor: ZhangXingKai；GuoJianZhong
School: Capital University of Economics
Course: Occupational and Environmental Health
Keywords: Hazardous chemicals vehicles Tankers PCA BP neural network MATLAB Training Identification
CLC: U492.8
Type: Master's thesis
Year: 2006
Downloads: 709
Quote: 4
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Abstract


As China 's economic development, transport of dangerous chemicals increased year by year , the use of tools such as tankers carrying dangerous chemicals in transport plays an important role . Vehicles transporting hazardous chemicals through the city or town in the district , the event of an accident , the consequences of significant influence. In order to reduce vehicle transport accidents of dangerous chemicals and the resulting loss in key conservation targets and personnel -intensive sensitive sections , to take a specific period of dangerous chemicals banned vehicle traffic measures are necessary to implement these measures , we must first solve vehicle identification of hazardous chemicals is the question . This paper analyzes the characteristics of hazardous tanker transport vehicles , based on the study of image preprocessing, edge detection, PCA feature extraction as well as the principle of BP neural network algorithm , structure and selection of the initial value problems is studied based on PCA and BP neural network algorithm tanker identification mode , the process and the image processing method . VB and MATLAB applications written computer program , forming a tanker based on PCA feature and BP neural network algorithm recognition system. The system is able to complete the tanker image preprocessing , PCA feature extraction , BP neural network training and identification based on BP neural network and other functions .

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CLC: > Transportation > Road transport > Technical management of traffic engineering and road transport > Operation Technology > Road transport safety technology
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