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Date of Publication:2018-01-01

Journal:大连理工大学学报

Affiliation of Author(s):运载工程与力学学部

Volume:58

Issue:2

Page Number:194-201

ISSN No.:1000-8608

Abstract:The generation of driver fatigue is a progressive dynamic process.Relevant research based on hidden Markov model (HMM)must determine the model's initial values firstly and the training process tends to fall into local optimum.Therefore,particle swarm optimization (PSO)algorithm is introduced into the process of training HMM to improve the above existing problems.What's more, the improved method and forward-backward (BW)algorithm are compared in details based on typical driver fatigue data set.Experimental and analytical test results show that the improved method is more accurate and stable than BW algorithm in driver fatigue prediction.

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