基于新陈代谢灰色马尔科夫的应急物资需求量预测方法

doi:10.16182/j.issn1004731x.joss.21-0874

系统仿真学报 ›› 2023, Vol. 35 ›› Issue (2): 229-240.doi: 10.16182/j.issn1004731x.joss.21-0874

• 论文 • 下一篇

基于新陈代谢灰色马尔科夫的应急物资需求量预测方法

马龙¹(), 秦宝东²(), 卢娜¹, 寇猛¹

^1.西安航空学院经济管理学院，陕西西安 710077
^2.西安邮电大学网络空间安全学院，陕西西安 710121

收稿日期:2021-08-29 修回日期:2021-10-12 出版日期:2023-02-28 发布日期:2023-02-16
通讯作者: 秦宝东 E-mail:malong1982@126.com;qinbaodong@xupt.edu.cn
作者简介:马龙(1982-)，男，副教授，博士，研究方向为计算智能、应急物资车辆路径优化、应急管理。E-mail：malong1982@126.com
基金资助:
国家自然科学基金(61872292);陕西省科技厅软科学计划(2021KRM154);陕西省体育局科研计划(2021439)

Demand Forecasting Method of Emergency Materials Based on Metabolic Gray Markov

Long Ma¹(), Baodong Qin²(), Na Lu¹, Meng Kou¹

^1.School of Economics and Management, Xi'an Aeronautical University, Xi'an 710077, China
^2.School of Cyberspace Security, Xi'an University of Posts & Telecommunications, Xi'an 710121, China

Received:2021-08-29 Revised:2021-10-12 Online:2023-02-28 Published:2023-02-16
Contact: Baodong Qin E-mail:malong1982@126.com;qinbaodong@xupt.edu.cn

摘要/Abstract

摘要：

为提高受灾人数与应急物资需求量预测精度问题，提出了基于新陈代谢灰色马尔科夫的应急物资需求量预测 方法。依据应急物资需求量预测思路，利用灰色、马尔科夫和新陈代谢理论，层级递进地构建新陈代谢灰色马尔科夫预测模型，实现受灾人数的动态预测；利用安全库存理论，构建应急物资柔性需求预测模型，实现受灾人数与物资需求量的供需平衡问题；运用本文模型、灰色马尔科夫模型和灰色模型对受灾人数与物资需求量进行预测，结果表明：该预测模型的相对误差要比其他模型小0.002 1%，预测精度明显优于基本的灰色模型，预测的受灾人口数量与应急物资需求量拟合度较高。

关键词: 新陈代谢灰色马尔科夫模型, 应急物资, 动态需求量, 洪涝灾害

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.

Key words: Metabolism-grey Markov model, emergency materials, dynamic demand, flood disaster

中图分类号:

TP391.9

马龙, 秦宝东, 卢娜, 寇猛. 基于新陈代谢灰色马尔科夫的应急物资需求量预测方法[J]. 系统仿真学报, 2023, 35(2): 229-240.

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.

图/表 13

图1

表1

表2

图2

表3

表4

图3

表5

图4

图5

表6

应急物资需求量预测的参数值

变量	值	变量	值
$α 1$ /kg	2 500	$α 5$ /条	0.50
$α 2$ /kg	1.60	$L$ /d	1.00
$α 3$ /支	1.66	$∂$	0.05
$α 4$ /顶	0.25	$Z 1 - ∂$	1.65

表6

图6

图7

参考文献 16

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第几天	受灾人数	第几天	受灾人数
1	4.66	7	58.73
2	7.90	8	66.48
3	22.25	9	112.23
4	24.33	10	122.55
5	36.46	11	157.78
6	57.33	12	185.80

第几天	实际值/万人	基本GM(1， N) 模型		GM(1， N)残差修正
第几天	实际值/万人	预测值 /万人	相对误差/%	预测值 /万人	相对误差/%
平均相对误差			0.031 8		0.42
1	4.66	4.66	─	5.08	─
2	7.90	8.23	0.000 6	7.90	-14.00
3	22.25	22.73	0.001 3	25.94	4.82
4	24.33	28.91	0.001 9	32.65	-0.90
5	36.46	36.53	0.002 0	41.09	-0.07
6	57.33	52.21	0.089 2	51.72	5.12
7	58.73	61.85	0.053 1	65.09	-3.12
8	66.48	62.68	0.057 1	81.92	3.80
9	112.23	100.69	0.102 8	103.11	11.54
10	122.55	126.63	0.033 3	129.77	-4.08
11	157.78	157.40	0.002 4	163.33	0.38
12	185.80	184.64	0.006 2	205.57	1.16

第几天	相对误差/%	状态分布
1	─	─
2	-14	S₁
3	4.82	S₅
4	-0.9	S₁
5	-0.07	S₁
6	5.12	S₅
7	-3.12	S₁
8	3.80	S₅
9	11.54	S₅
10	-4.08	S₁
11	0.38	S₃
12	1.16	S₅

方法	第几天	实际值/万人	预测值/万人	相对误差/%
灰色模型	13	197.83	211.93	0.007 4
	14	237.16	242.69	0.007 9
	15	251.33	259.17	0.006 8
灰色马尔科夫模型	13	197.83	198.71	0.006 9
	14	237.16	238.71	0.007 0
	15	251.33	259.44	0.009 5
新陈代谢灰色马尔科夫模型	13	197.83	─	─
	14	237.16	224.16	0.008 1
	15	251.33	237.92	0.008 9

第几天	实际值	文献[7]预测值	本文模型预测值
1	4.66	─	─
2	7.90	7.90	7.90
3	22.25	25.94	23.89
4	24.33	32.65	28.17
5	36.46	41.09	40.13
6	57.33	51.72	55.81
7	58.73	65.09	57.26
8	66.48	81.92	74.37
9	112.23	103.11	110.64
10	122.55	129.77	126.05
11	157.78	163.33	160.27
12	185.80	205.57	198.91

基于新陈代谢灰色马尔科夫的应急物资需求量预测方法

Demand Forecasting Method of Emergency Materials Based on Metabolic Gray Markov

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