Traffic Information Network Based on Internet of Things
發(fā)布時(shí)間:2022-12-07 04:19
With the development of advanced technologies such as computer technology,network technology and sensor technology,based on the internet.The expansion and extension of the foundation formed a new generation of network technology that the Internet of things(for short as IOT)The Internet of Things is a major development opportunity facing mankind in the 21 st century.The Internet of Things will be widely used is the second computer,the Internet and mobile communications network after another revol...
【文章頁(yè)數(shù)】:144 頁(yè)
【學(xué)位級(jí)別】:碩士
【文章目錄】:
Abstract
Declaration
Acknowledgements
Dedication
List of Abbreviations and Symbols
Chapter 1: Introduction
1.1 Research Background and Significance
1.1.1 Background
1.1.2 The significance of research
1.2 Research Summary at Home (China) and Abroad
1.2.1 Research Status at Home and Abroad
1.2.2 Domestic and Foreign Research Review
1.3 Main research content and research ideas
1.3.1 Research Content
1.3.2 Research Ideas
Chapter 2: LITERATURE REVIEW What is Internet of Things and what is traffic information network? How to combine the internet of things with trafficinformation?
2.1 What is internet of things
2.1.1 What is Traffic Information Network
2.2. Overview of Regional Traffic Information Network
2.2.1. Development Status of Traffic Information Network
2.2.2. Problems with Regional Traffic Information Network
2.2.3. Internet of Things and Its Application Prospects in Transportation
2.2.4. Concept of the Internet of Things
2.2.5. Features of the Internet of Things
2.2.6. Analysis of Application Prospect of Internet of Things in Transportation Fiel
2.3 IOT-based Regional Traffic Information Network
2.3.1 Positioning of Traffic Information Network
2.3.2 Hierarchy of Traffic Information Network
2.3.3 Traffic Information Network Architecture
2.4 Summary of this chapter
Chapter 3: METHODOLOGY The volume of the traffic information networkprediction
3.1 Traffic Information Requirements and Features
3.1.1 traffic information needs analysis
3.1.2 Demand characteristics of traffic information
3.2 Basic Ideas for Traffic Information Demand Forecast Based on Four-phase Method
3.2.1 Overview of the Four-Stage Approach
3.2.2 The mother of the demand forecast and related principles
3.2.3 Four- phase method for forecasting traffic information demand
3.3 Traffic Information Demand Forecasting Model Based on Four-phase Method
3.3.1 Traffic Information Generation Forecast
3.3.2 Traffic Information Distribution Forecast
3.3.3 Traffic Information Sharing Forecast
3.3.4 Traffic Information Allocation Forecast
3.4 Summary of this chapter
Chapter 4: Optimization of multi-attribute Internet of Things based Traffic Information Network layout
4.1 Regional Traffic Information Network Layout
4.1.1 Regional Traffic Information Network Layout Target
4.1.2 Principles of Regional Traffic Information Network Layout
4.2 Hole Structure and Features
4.2.1 Cellular Network Layout Mode
4.2.2 Structure and Features of the Cellular Network Layout Model
4.2.3 Applicable conditions for the mesh network layout mode
4.3 Ring Network Layout Mode and Features
4.3.1 Ring Network Layout Mode
4.3.2 Structure and Features of the Ring Network Layout Mode
4.3.3 Applicable Conditions for the Ring Network Layout Mode
4.4 Pivotal Network Layout Models and Features
4.4.1 Hub-type network layout mode
4.4.2 Structure and Features of Pivotal Network Layout Mode
4.4.3 Applicable Conditions for Pivotal Network Layout Mode
4.5 Summary of this chapter
Chapter 5 Chengdu City's Regional Traffic Information Network Layout Based on Internet of Things
5.1 Overview of Chengdu Traffic Information Network
5.2 Chengdu City Traffic Information Network Layout Ideas and Principles
5.2.1 Ideas and Goals of Optimizing Network Layout
5.2.2 Principles of Network Layout Optimization
5.2.3 Network Layout Optimization Evaluation Procedure
5.3 Construction of Index System of Chengdu Network Layout Model
5.3.1 Principles for Establishing Evaluation Indicators
5.3.2 Establishment of evaluation index system
5.4 Chengdu Traffic Information Demand Forecast
5.4.1 Chengdu City Traffic Information Generation Forecast
5.4.2 Traffic Information Distribution Forecast
5.4.3 Traffic Information Allocation Forecast
5.5 Distribution of Chengdu Traffic Information Network
5.6 Summary of this chapter
5.6.1 Recommendations
5.6.2 Objectives and Contribution of this Project
5.6.3 Conclusion
References
APPENDIX
【參考文獻(xiàn)】:
期刊論文
[1]交通物聯(lián)網(wǎng)的系統(tǒng)架構(gòu)與技術(shù)體系[J]. 賴(lài)宏圖,朱銓,蔣新華,鄒復(fù)民. 福建工程學(xué)院學(xué)報(bào). 2015(01)
[2]一種虛擬交通環(huán)境中的微觀交通仿真模型[J]. 劉東輝,蘇虎. 西南交通大學(xué)學(xué)報(bào). 2013(01)
[3]經(jīng)濟(jì)圈交通網(wǎng)絡(luò)SVM評(píng)價(jià)方法[J]. 張兵,鄧衛(wèi). 東南大學(xué)學(xué)報(bào)(自然科學(xué)版). 2012(06)
[4]一種基于TOPSIS的混合型多屬性群決策方法[J]. 梁昌勇,戚筱雯,丁勇,冷亞軍. 中國(guó)管理科學(xué). 2012(04)
[5]基于物聯(lián)網(wǎng)的智能交通流探測(cè)技術(shù)研究[J]. 劉唐,彭艦,楊進(jìn),汪小芬. 計(jì)算機(jī)科學(xué). 2011(09)
[6]京津冀區(qū)域鐵路交通網(wǎng)絡(luò)結(jié)構(gòu)評(píng)價(jià)[J]. 朱桃杏,吳殿廷,馬繼剛,趙莉琴. 經(jīng)濟(jì)地理. 2011(04)
[7]交通影響分析中交通需求預(yù)測(cè)探討[J]. 王冠軍. 科學(xué)技術(shù)與工程. 2010(21)
[8]基于元胞傳輸模型的區(qū)域疏散動(dòng)態(tài)交通分配[J]. 崔建勛,安實(shí),崔娜. 哈爾濱工業(yè)大學(xué)學(xué)報(bào). 2010(01)
[9]道路交通網(wǎng)絡(luò)效率定量評(píng)價(jià)方法及其應(yīng)用[J]. 秦進(jìn),史峰,鄧連波,肖龍文. 吉林大學(xué)學(xué)報(bào)(工學(xué)版). 2010(01)
[10]基于神經(jīng)網(wǎng)絡(luò)的城市交通流預(yù)測(cè)研究[J]. 馬君,劉小冬,孟穎. 電子學(xué)報(bào). 2009(05)
本文編號(hào):3712222
【文章頁(yè)數(shù)】:144 頁(yè)
【學(xué)位級(jí)別】:碩士
【文章目錄】:
Abstract
Declaration
Acknowledgements
Dedication
List of Abbreviations and Symbols
Chapter 1: Introduction
1.1 Research Background and Significance
1.1.1 Background
1.1.2 The significance of research
1.2 Research Summary at Home (China) and Abroad
1.2.1 Research Status at Home and Abroad
1.2.2 Domestic and Foreign Research Review
1.3 Main research content and research ideas
1.3.1 Research Content
1.3.2 Research Ideas
Chapter 2: LITERATURE REVIEW What is Internet of Things and what is traffic information network? How to combine the internet of things with trafficinformation?
2.1 What is internet of things
2.1.1 What is Traffic Information Network
2.2. Overview of Regional Traffic Information Network
2.2.1. Development Status of Traffic Information Network
2.2.2. Problems with Regional Traffic Information Network
2.2.3. Internet of Things and Its Application Prospects in Transportation
2.2.4. Concept of the Internet of Things
2.2.5. Features of the Internet of Things
2.2.6. Analysis of Application Prospect of Internet of Things in Transportation Fiel
2.3 IOT-based Regional Traffic Information Network
2.3.1 Positioning of Traffic Information Network
2.3.2 Hierarchy of Traffic Information Network
2.3.3 Traffic Information Network Architecture
2.4 Summary of this chapter
Chapter 3: METHODOLOGY The volume of the traffic information networkprediction
3.1 Traffic Information Requirements and Features
3.1.1 traffic information needs analysis
3.1.2 Demand characteristics of traffic information
3.2 Basic Ideas for Traffic Information Demand Forecast Based on Four-phase Method
3.2.1 Overview of the Four-Stage Approach
3.2.2 The mother of the demand forecast and related principles
3.2.3 Four- phase method for forecasting traffic information demand
3.3 Traffic Information Demand Forecasting Model Based on Four-phase Method
3.3.1 Traffic Information Generation Forecast
3.3.2 Traffic Information Distribution Forecast
3.3.3 Traffic Information Sharing Forecast
3.3.4 Traffic Information Allocation Forecast
3.4 Summary of this chapter
Chapter 4: Optimization of multi-attribute Internet of Things based Traffic Information Network layout
4.1 Regional Traffic Information Network Layout
4.1.1 Regional Traffic Information Network Layout Target
4.1.2 Principles of Regional Traffic Information Network Layout
4.2 Hole Structure and Features
4.2.1 Cellular Network Layout Mode
4.2.2 Structure and Features of the Cellular Network Layout Model
4.2.3 Applicable conditions for the mesh network layout mode
4.3 Ring Network Layout Mode and Features
4.3.1 Ring Network Layout Mode
4.3.2 Structure and Features of the Ring Network Layout Mode
4.3.3 Applicable Conditions for the Ring Network Layout Mode
4.4 Pivotal Network Layout Models and Features
4.4.1 Hub-type network layout mode
4.4.2 Structure and Features of Pivotal Network Layout Mode
4.4.3 Applicable Conditions for Pivotal Network Layout Mode
4.5 Summary of this chapter
Chapter 5 Chengdu City's Regional Traffic Information Network Layout Based on Internet of Things
5.1 Overview of Chengdu Traffic Information Network
5.2 Chengdu City Traffic Information Network Layout Ideas and Principles
5.2.1 Ideas and Goals of Optimizing Network Layout
5.2.2 Principles of Network Layout Optimization
5.2.3 Network Layout Optimization Evaluation Procedure
5.3 Construction of Index System of Chengdu Network Layout Model
5.3.1 Principles for Establishing Evaluation Indicators
5.3.2 Establishment of evaluation index system
5.4 Chengdu Traffic Information Demand Forecast
5.4.1 Chengdu City Traffic Information Generation Forecast
5.4.2 Traffic Information Distribution Forecast
5.4.3 Traffic Information Allocation Forecast
5.5 Distribution of Chengdu Traffic Information Network
5.6 Summary of this chapter
5.6.1 Recommendations
5.6.2 Objectives and Contribution of this Project
5.6.3 Conclusion
References
APPENDIX
【參考文獻(xiàn)】:
期刊論文
[1]交通物聯(lián)網(wǎng)的系統(tǒng)架構(gòu)與技術(shù)體系[J]. 賴(lài)宏圖,朱銓,蔣新華,鄒復(fù)民. 福建工程學(xué)院學(xué)報(bào). 2015(01)
[2]一種虛擬交通環(huán)境中的微觀交通仿真模型[J]. 劉東輝,蘇虎. 西南交通大學(xué)學(xué)報(bào). 2013(01)
[3]經(jīng)濟(jì)圈交通網(wǎng)絡(luò)SVM評(píng)價(jià)方法[J]. 張兵,鄧衛(wèi). 東南大學(xué)學(xué)報(bào)(自然科學(xué)版). 2012(06)
[4]一種基于TOPSIS的混合型多屬性群決策方法[J]. 梁昌勇,戚筱雯,丁勇,冷亞軍. 中國(guó)管理科學(xué). 2012(04)
[5]基于物聯(lián)網(wǎng)的智能交通流探測(cè)技術(shù)研究[J]. 劉唐,彭艦,楊進(jìn),汪小芬. 計(jì)算機(jī)科學(xué). 2011(09)
[6]京津冀區(qū)域鐵路交通網(wǎng)絡(luò)結(jié)構(gòu)評(píng)價(jià)[J]. 朱桃杏,吳殿廷,馬繼剛,趙莉琴. 經(jīng)濟(jì)地理. 2011(04)
[7]交通影響分析中交通需求預(yù)測(cè)探討[J]. 王冠軍. 科學(xué)技術(shù)與工程. 2010(21)
[8]基于元胞傳輸模型的區(qū)域疏散動(dòng)態(tài)交通分配[J]. 崔建勛,安實(shí),崔娜. 哈爾濱工業(yè)大學(xué)學(xué)報(bào). 2010(01)
[9]道路交通網(wǎng)絡(luò)效率定量評(píng)價(jià)方法及其應(yīng)用[J]. 秦進(jìn),史峰,鄧連波,肖龍文. 吉林大學(xué)學(xué)報(bào)(工學(xué)版). 2010(01)
[10]基于神經(jīng)網(wǎng)絡(luò)的城市交通流預(yù)測(cè)研究[J]. 馬君,劉小冬,孟穎. 電子學(xué)報(bào). 2009(05)
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