Study of Equipment Material Demand Prediction Method Based on Time-continuous Grey Markov Model

doi:10.3969/j.issn.1000-1093.2017.09.025

Abstract

Abstract: The time continuous and state discrete grey Markov model is used to predict the demand of equipment maintenance materials. The state intervals are set according to the changing amplitude and distribution of consumed maintenance materials. The one-step Markov transition matrix is calculated by states transition. Kolmogorov differential equations are used to solve the time functions of state probabilities and establish the prediction equations of state probabilities. The grey positioning coefficient is determined from the probability values of predicted states. The case analysis shows that the prediction accuracy of the improved grey Markov model is higher than those of GM(1, 1) model, traditional grey Markov residual error correction model and grey Markov chain model. Its validity and practicability were proven during the prediction of equipment material demand.Key

Key words: ordnancescienceandtechnology, Markovmodel, greypredictionmodel, Kolmogorovdifferentialeauation, predictionaccuracy

CLC Number:

ZHANG Lei, LI Shi-min, ZHU Gang. Study of Equipment Material Demand Prediction Method Based on Time-continuous Grey Markov Model[J]. Acta Armamentarii, 2017, 38(9): 1862-1866.

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第38卷
第9期2017 年9月兵工学报ACTA
ARMAMENTARIIVol.38No.9Sep.2017

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