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In this paper, a novel framework and methodology based on hidden semi-Markov models (HSMMs) for high PM 2.5 concentration value prediction is presented. Due to lack of explicit time structure and its short-term memory of past history, a standard hidden Markov model (HMM) has limited power in mod-eling the temporal structures of the prediction problems. To(More)
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