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When LoRa meets distributed machine learning to optimize the network connectivity for green and intelligent transportation system

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green Energy and Intelligent transportation 2024年第3期3卷 24-41页

作者： Malak Abid Ali Khan Hongbin Ma Arshad Farhad Asad Mujeeb Imran Khan Mirani Muhammad Hamza National Key Lab of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Department of Computer Science Namal UniversityPakistan Department of Electrical Engineering Tsinghua UniversityBeijing 100084China Faculty of Information Technology Beijing University of TechnologyBeijing 100124China School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China

LoRa technology contributes to green energy by enabling efficient,long-range communication for the Internet of Things(IoT).This paper addresses the challenges related to coverage range in outdoor monitoring systems utilizing LoRa,where the network performance is affected by the density of gateways(GWs)and end devices(EDs),as well as environmental *** mitigate interference,data throughput losses,and high-power consumption,the proposed spreading factor(SF)and hybrid(data rate|SF)models dynamically adjust the transmission *** orchestration of concurrent data modifications within the network server(NS)is crucial for uninterrupted communication between GWs and EDs,especially in monitoring electric vehicle(EV)stations to reduce traffic congestion and *** K-means and density-based spatial clustering of applications with noise(DBSCAN)algorithms optimizes ED allocation,averts data congestion,and improves the signal-tointerference noise ratio(SINR).These methods ensure seamless information reception by meticulously allocated EDs across various GW *** estimate the free-space losses(FSL),a log-distance path loss model(log-PL)is *** various bandwidths(BWs),bidirectional communications,and duty cycles(DCs)helps to prevent saturation,thus prolonging the operational lifespan of *** findings reveal a notable packet rejection rate(PRR)of 0%for the DBSCAN(hybrid model).In contrast,the K-means exhibits a PRR ranging from 5%(hybrid model)to 35.29%(SF model)for the ten GWs ***,the network saturation is reduced to 10.185%and 9.503%,respectively,highlighting an improvement in the average efficiency of slotted ALOHA(91.1%)and pure ALOHA(90.7%).These enhancements increase the lifespan of EDs to 15,465.27 days.

关键词： DBSCAN green transportation Hybrid model Intelligent transportation K-means

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Analysis on Urban Traffic Congestion

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校园英语 2017年第40期 240-241页

作者：王紫 Chengdu Shishi Middle School(Beihu) 2018 Session

With the acceleration of urbanization and motorization,as well as the enhancement of population, urban traffic congestion has become more serious and had an influence on people’s normal life. The author thinks it exists imbalance between the supply and demand of urban transport, and unreasonable traffic route planning and transportation management also aggravate traffic jam. This paper mainly explores the major causes and harms of traffic jam, and proposes some suggestions to alleviate traffic congestion and establish a harmonious relationship between residents and transport.

关键词： traffic congestion green transportation urban development

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green Innovation for Urban Traffic

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Frontiers of Engineering Management 2015年第1期2卷 35-38页

作者： Yu Zhao Sheng-quan Wang Ke-chao Zhu School of Economics and Management Shanghai Institute of Technology

With the development of economy, the issue of urban traffic is becoming highlighted, the pollution of the urban traffic has become one of the main factors to in fluence environment. It faces the broader problem of achieving sustainable development of urban transportation at present. The current situation of urban traffic is analyzed through studying the existing articles at home and abroad in this paper; the problems such as green innovation of urban traffic are elaborated. In addition, this paper puts forward the relevant measures to promote the development of green innovation of the urban traffic.

关键词： urban traffic green innovation green transportation sustainable development

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