Fady Samann1,2,*, Shavan Askar3
CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2421-2444, 2024, DOI:10.32604/cmes.2023.031265
Abstract Implementing machine learning algorithms in the non-conducive environment of the vehicular network requires some adaptations due to the high computational complexity of these algorithms. K-clustering algorithms are simplistic, with fast performance and relative accuracy. However, their implementation depends on the initial selection of clusters number (K), the initial clusters’ centers, and the clustering metric. This paper investigated using Scott’s histogram formula to estimate the K number and the Link Expiration Time (LET) as a clustering metric. Realistic traffic flows were considered for three maps, namely Highway, Traffic Light junction, and Roundabout junction, to study the effect of road layout on… More >
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