List of Articles traffic management

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  1 - DTMP: Energy Consumption Reduction in Body Area Networks Using a Dynamic Traffic Management Protocol
  Mona Alimardani Amir Masoud Rahmani Houman Zarrabi
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  2 - Studying the Strategies of Traffic Reduction in Tehran
  iman alibeyk nadi alizadeh ali hojati
  Because the phenomenon of urban residing has grown incredibly and the number of cars has increased in cities, we witness a day to day exponential growth of traffic in the big city of Tehran which has become the main problem of its urban managers. In this paper, the rese More

  Because the phenomenon of urban residing has grown incredibly and the number of cars has increased in cities, we witness a day to day exponential growth of traffic in the big city of Tehran which has become the main problem of its urban managers. In this paper, the researcher has studied the causes of traffic in Tehran today and has offered solutions to reduce traffic in the world which includes methods of traffic restriction and the idea that permits cars with odd plates to be used on odd days and cars with even plates are allowed to be used on even days with the aim to reduce traffic in Tehran and the management of traffic. The researcher has then studied the current strategies of traffic reduction and its effects with the aim to provide new solutions for it and has also studied the role of IT in traffic control, the education of proper traffic behaviors and traffic regulations. Manuscript profile
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  3 - Communication-Aware Traffic Stream Optimization for Virtual Machine Placement in Cloud Datacenters with VL2 Topology
  Sara Farzai Mirsaeid Hosseini Shirvani Mohsen Rabbani
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  4 - The Importance and Necessity of Lack of Delay in Exchange of Information and Data of Intelligent Transportation Systems
  Ali Mohebi Mehdi Yar Mohammadi Farnaz Kheibari Esmaeil Alizadeh
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  5 - Possibility of the Economic Prediction Model based on the Smart Algorithm of the Smart City
  mahsa khodadadi Larissa Khodadadi روزبه دبیری
  Smart cities make better use of space and have less traffic, cleaner air and more efficient city services and improve people's quality of life. The large number of vehicles that are constantly moving through congested areas in smart cities complicates the availability o More

  Smart cities make better use of space and have less traffic, cleaner air and more efficient city services and improve people's quality of life. The large number of vehicles that are constantly moving through congested areas in smart cities complicates the availability of a public parking space. This creates challenges for both traffic and residents. With such a large population, road congestion is a serious challenge. It wastes vital resources like fuel, money and most importantly time. Finding a suitable place to park is one of the reasons for traffic jams on highways. This paper proposes an economic forecasting model based on deep learning for long-term economic growth in smart cities. Traffic management is vital for cities in that it ensures that people can move freely around the city. Many cars trying to reach congested areas in smart cities make it difficult to find a public parking lot. This issue is inconvenient for both drivers and residents. A number of traffic management authorities have implemented an artificial neural network to solve this problem, and modern car systems have come with smart parking solutions. The experimental result of the economic forecasting model based on deep learning improves traffic estimation, accurate prediction of traffic flow, traffic management and intelligent parking compared to existing methods Manuscript profile