發(fā)布時間：2018-03-24 19:34

  本文選題：車載視頻　切入點(diǎn)：變流量傳輸　出處：《浙江工業(yè)大學(xué)》2014年碩士論文

【摘要】：隨著社會經(jīng)濟(jì)和科技的不斷發(fā)展,公路運(yùn)輸在給人類生活帶來便利的同時,影響交通運(yùn)輸安全的惡性事件時有發(fā)生,公路交通治安問題儼然成為公路運(yùn)輸業(yè)和公安系統(tǒng)的難題。視頻作為信息載體,已成為公路交通監(jiān)控中的一種主要方式。然而當(dāng)前基于移動公網(wǎng)的信息傳輸流量費(fèi)用仍然較高,本文研究基于信息融合的車載視頻信息變流量傳輸算法,可有效降低昂貴的流量費(fèi)用,主要工作和成果如下：(1)分析信息融合和BP (Back-Propagation,反向傳播)神經(jīng)網(wǎng)絡(luò)的優(yōu)缺點(diǎn),針對BP網(wǎng)絡(luò)的輸入信息復(fù)雜多變時,固定的網(wǎng)絡(luò)結(jié)構(gòu)不能適應(yīng)各種變化的環(huán)境的問題,提出了結(jié)合DS (Dempster-Shafe r證據(jù)理論)和BP神經(jīng)網(wǎng)絡(luò)的決策算法,即DS-]BP決策算法。(2)通過研究車輛運(yùn)行異常的原因,對車輛的視頻、音頻、車速、加速度、轉(zhuǎn)向強(qiáng)度、發(fā)動機(jī)轉(zhuǎn)速和冷卻液溫度等信息進(jìn)行異常特征提取,為之后的車載視頻變流量傳輸決策奠定數(shù)據(jù)基礎(chǔ)。(3)利用PSO (Particle Swarm Optimization,粒子群優(yōu)化)算法來確定BP神經(jīng)網(wǎng)絡(luò)的初值,改善了BP神經(jīng)網(wǎng)絡(luò)容易陷入局部極小值和收斂速度慢的問題。
[Abstract]:With the continuous development of social economy and science and technology, highway transportation brings convenience to human life, and at the same time, the malignant events that affect the safety of transportation occur from time to time. The problem of highway traffic security has become a difficult problem in highway transportation and public security system. As a carrier of information, video has become a main way of highway traffic monitoring. However, the cost of information transmission based on mobile public network is still relatively high. This paper studies the variable traffic transmission algorithm based on information fusion, which can effectively reduce the high traffic cost. The main work and results are as follows: 1) analyzing the advantages and disadvantages of information fusion and BP Back-Propagation) neural network. In view of the problem that the fixed network structure can not adapt to various changing environments when the input information of BP network is complex and changeable, a decision algorithm based on DS Dempster-Shafe r evidence theory and BP neural network is proposed. That is, DS-] BP decision algorithm. 2) by studying the cause of the abnormal operation of the vehicle, the abnormal features of the video, audio, speed, acceleration, steering strength, engine speed and coolant temperature of the vehicle are extracted. This paper establishes the data base for the later decision of vehicle video variable traffic transmission. It uses PSO / Particle Swarm optimization (PSO) algorithm to determine the initial value of BP neural network, which improves the problem that BP neural network is easy to fall into local minimum value and slow convergence speed.
【學(xué)位授予單位】：浙江工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：U495;TP202
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本文編號：1659725