Cheng Gong1,2, Xinzhu Yang1, Wei Huangfu3,4,*, Qinghua Lu5
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2445-2457, 2021, DOI:10.32604/cmc.2021.016713
Abstract Communication opportunities among vehicles are important for data transmission over the Internet of Vehicles (IoV). Mixture models are appropriate to describe complex spatial-temporal data. By calculating the expectation of hidden variables in vehicle communication, Expectation Maximization (EM) algorithm solves the maximum likelihood estimation of parameters, and then obtains the mixture model of vehicle communication opportunities. However, the EM algorithm requires multiple iterations and each iteration needs to process all the data. Thus its computational complexity is high. A parameter estimation algorithm with low computational complexity based on Bin Count (BC) and Differential Evolution (DE) (PEBCDE) is proposed. It overcomes the… More >
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