Journal of System Simulation
Abstract
Abstract: In order to improve the prediction accuracy of the demand for emergency materials of people affected by the disaster, a forecasting method based on metabolism-gray Markov's is proposed. To realize the dynamic prediction of the number of people affected by the disaster, according to demand forecast ideas, the prediction model of metabolism-gray Markov fused is constructed progressively through gray, Markov and metabolism theories. A flexible demand forecasting model for emergency supplies is built through safety stock theory to complete the balance of supply and demand between people number and the materials demand. The prediction results of different models show that the relative error of the proposed prediction model is 0.002 1% smaller better than other models, and the prediction accuracy is significantly better than that of the gray model, in which the prediction of the number of people affected by disasters and the demand for emergency supplies have a higher fit degree.
Recommended Citation
Ma, Long; Qin, Baodong; Lu, Na; and Kou, Meng
(2023)
"Demand Forecasting Method of Emergency Materials Based on Metabolic Gray Markov,"
Journal of System Simulation: Vol. 35:
Iss.
2, Article 1.
DOI: 10.16182/j.issn1004731x.joss.21-0874
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol35/iss2/1
First Page
229
Revised Date
2021-10-12
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.21-0874
Last Page
240
CLC
TP391.9
Recommended Citation
Long Ma, Baodong Qin, Na Lu, Meng Kou. Demand Forecasting Method of Emergency Materials Based on Metabolic Gray Markov[J]. Journal of System Simulation, 2023, 35(2): 229-240.
DOI
10.16182/j.issn1004731x.joss.21-0874
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