基于ISSA-BP的地震灾害救援装备需求预测

doi:10.16265/j.cnki.issn1003-3033.2025.S1.0037

中国安全科学学报 ›› 2025, Vol. 35 ›› Issue (S1): 246-251.doi: 10.16265/j.cnki.issn1003-3033.2025.S1.0037

基于ISSA-BP的地震灾害救援装备需求预测

刘浩¹(), 石福丽², 罗雷², 李文博³, 李文渊⁴

¹ 中国人民武装警察部队工程大学研究生大队, 陕西西安 710086
² 中国人民武装警察部队工程大学装备管理与保障学院, 陕西西安 710086
³ 甘肃省地震局, 甘肃兰州 730000
⁴ 中国刑事警察学院警犬技术学院, 辽宁沈阳 110854

收稿日期:2025-01-14 修回日期:2025-03-17 出版日期:2025-09-03
作者简介:
刘浩 (1988—),男,陕西延安人,硕士研究生,主要研究方向为地震地质灾害应急救援理论与技术。E-mail:360044354@qq.com。
石福丽, 讲师
罗雷, 副教授
李文渊, 讲师
基金资助:
项目基金:武警部队装备综合研究项目(WJ2022B030300); 项目基金:武警部队装备综合研究项目(WJ2023A010400); 陕西省自然科学基础研究计划青年人才项目(2015JQ6224); 武警工程大学军事理论综合研究项目(JLY2024100); 武警工程大学军事理论综合研究项目(JLY2024109)

Demand prediction of earthquake disaster rescue equipment based on ISSA-BP

LIU Hao¹(), SHI Fuli², LUO Lei², LI Wenbo³, LI Wenyuan⁴

¹ Graduate Regiment, Engineering University of People's Armed Police, Xi'an Shaanxi 710086, China
² College of Equipment Management and Support, Engineering University of People's Armed Police, Xi'an Shaanxi 710086, China
³ Gansu Earthquake Agency, Lanzhou Gansu 730000, China
⁴ Police Dog Technical College, Criminal Investigation Police University of China, Shenyang Liaoning 110854, China

Received:2025-01-14 Revised:2025-03-17 Published:2025-09-03

摘要/Abstract

摘要： 为提高地震救援装备调配保障效率,分析国内历史地震救援信息,以受灾人数为预测对象,选取震级、震源深度、地震烈度等8个灾情信息为影响因素,提出一种基于反向传播(BP)神经网络并融合空间金字塔匹配(SPM)混沌映射、正余弦算法和Levy飞行策略的改进麻雀搜索算法(ISSA)的预测模型,结合受灾人数与救援装备间的数量关系,间接预测地震救援装备需求量,并以“12·18积石山地震”救援实例进行验证。结果表明:ISSA-BP模型在预测受灾人数方面精度更高,可有效预测震后受灾人数,从而推算所需救援装备数量。“12·18积石山地震”救援实例验证了模型对震后救援装备需求预测的实用性。

关键词: 改进麻雀优化算法(ISSA), 反向传播(BP), 地震灾害, 救援装备, 需求预测

Abstract:

To enhance the efficiency of earthquake rescue equipment allocation and support, historical earthquake rescue information in China was analyzed, with the number of affected people as the prediction object and eight disaster information, such as magnitude, focal depth, and seismic intensity, as influencing factors. An ISSA based on BP neural network, spatial pyramid matching (SPM) chaotic mapping, sine-cosine algorithm, and Levy flight strategy was proposed. Combined with the quantitative relationship between the number of affected people and rescue equipment, the demand for earthquake rescue equipment was indirectly predicted. The ″12·18 Jishishan Earthquake″ rescue case was used for verification. The results show that the ISSA-BP model has higher accuracy in predicting the number of affected people and can effectively predict the number of affected people after an earthquake, thereby estimating the required rescue equipment. The ″12·18 Jishishan Earthquake″ rescue case verifies the practicality of the model in predicting the demand for rescue equipment after an earthquake.

Key words: improved sparrow search algorithm (ISSA), back propagation (BP), earthquake disaster, rescue equipment, demand prediction

中图分类号:

X915.5

刘浩, 石福丽, 罗雷, 李文博, 李文渊. 基于ISSA-BP的地震灾害救援装备需求预测[J]. 中国安全科学学报, 2025, 35(S1): 246-251.

LIU Hao, SHI Fuli, LUO Lei, LI Wenbo, LI Wenyuan. Demand prediction of earthquake disaster rescue equipment based on ISSA-BP[J]. China Safety Science Journal, 2025, 35(S1): 246-251.

图/表 6

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节点数	4	5	6	7	8
均方误差	0.049 34	0.097 13	0.068 393	0.063 79	0.072 56
节点数	9	10	11	12	13
均方误差	0.084 33	0.065 37	0.041 35	0.057 56	0.053 15

算法	均方误差	平均绝对误差	均方根误差
BP	12.286 6	2.682 8	3.505 2
SSA-BP	7.126 8	1.959 2	2.669 6
ISSA-BP	6.531 7	1.864 3	2.555 7

基于ISSA-BP的地震灾害救援装备需求预测

Demand prediction of earthquake disaster rescue equipment based on ISSA-BP

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