• DocumentCode
    3584664
  • Title

    Elicit the Best Ways through Identify Congestion Places

  • Author

    Alodat, Mohammad ; Abdullah, Iyas

  • Author_Institution
    Comput., Electr. & Electron. Eng., Univ. of Craiova, Craiova, Romania
  • fYear
    2014
  • Firstpage
    102
  • Lastpage
    107
  • Abstract
    In this paper the exploitation of infrastructure and take advantage of communication techniques wired and wireless to help drivers in finding ways does not contain any obstacles and reach to the target with commitment in speed of assessed road. We use Fusion or Polygamy Technology with Fuzzy Logic, Neural Network and Genetic Algorithm for extract Cut-Node (CN). We use Cut-Node (CN) in order to identify obstacles and avoid them such as changes that occur in the lighting, weather conditions, accidents, congestion and maintenance of roads. Cut-Node (CN) useful in understanding the surrounding environment, supporting safe driving, increases the flow and fastest path to arrive at the designated target (end point). Three models have been proposed to extract Cut-Node (CN) as follows: 1) Intuitionistic Fuzzy Set (IFS). 2) The Intuitionistic Fuzzy Set Data Base is representing imprecise data. 3) Intuitionistic Fuzzy Neural Network with Genetic Algorithm (IFNN-GA).
  • Keywords
    data structures; fuzzy set theory; genetic algorithms; neural nets; road safety; road traffic; traffic engineering computing; cut-node extraction; fusion technology; fuzzy logic; genetic algorithm; imprecise data representation; intuitionistic fuzzy neural network; intuitionistic fuzzy set; polygamy technology; road congestion places identification; safety driving; wired communication technique; wireless communication technique; Fuzzy logic; Fuzzy neural networks; Fuzzy sets; Genetic algorithms; Neurons; Roads; Vehicles; Cut Node; Fuzzy logic; Genetic algorithm; Intuitionistic Fuzzy Set; Neural networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Computer Science Applications and Technologies (ACSAT), 2014 3rd International Conference on
  • Type

    conf

  • DOI
    10.1109/ACSAT.2014.25
  • Filename
    7076877