基于BP神经网络的城市地震次生火灾起火率研究
详细信息 本馆镜像全文    |  推荐本文 | | 获取馆网全文
摘要
选取房屋破倒率、震时地面加速度峰值、地震区域抗震设防烈度和地震发生时刻作为引发地震次生火灾的4个预测因子,结合中美日76条地震次生火灾统计数据,运用BP神经网络建立城市地震次生火灾起火率预测模型。分别运用BP神经网络模型和国内二项式拟合模型对实际样本起火率进行预测。结果表明:BP神经网络模型的预测结果与样本的实际起火率基本吻合;与国内二项式拟合模型相比,BP模型在地震次生火灾起火率的预测精度上有了较大提高,证实了BP神经网络适用于地震次生火灾起火率预测。以武汉市汉口地区为例,对该地区地震次生火灾起火率进行了预测,为城市抗震救灾、消防设施布置和防灾减灾规划建立提供了依据。
Considering four predictors including house collapsed rate,peak ground acceleration,seismic fortification intensity and the time of earthquake,the BP neural network was used to establish the prediction model of frequency of urban post-earthquake fire with 76post-earthquake fire statistics from China,the United States and Japan.The BP neural network model and domestic binomial fitting model were employed to predict the frequency of fire in actual sample respectively.The experimental results indicated that the prediction of the BP neural network model coincided well with the actual frequency of fire in the sample.The prediction accuracy of BP neural network model was improved significantly compared with the domestic binomial fitting model,which meant BP neural network model was suitable for the prediction for frequency of post-earthquake fire.And taking Hankou area in Wuhan as a prediction object,the prediction for frequency of post-earthquake fire in this area was made,which aimed to provide the basis for earthquake relief,arrangement of firefighting devices and establishment of program for disaster prevention and reduction in city.
引文
[1]谢旭阳,任爱珠,刘铁民,等.基于GIS的地震次生火灾起火点预测[J].中国安全生产科学技术,2005,1(1):11-14.
    [2]Li Jie,Jiang Jianhua,Li Minghao.Hazard Analysis System of Urban Post-earthquake Fire Based on GIS[J].Acta Seismologica Sinica,2001,14(4):448-455.
    [3]李杰,李国强.地震次生火灾预测模型研究[J].中国地震,1992,8(1):76-82.
    [4]马东辉,郭小东,王志涛.城市抗震防灾规划标准实施指南[M].北京:中国建筑工业出版社,2008.
    [5]余世舟.地震次生灾害的数值模拟[D].哈尔滨:中国地震局工程力学研究所,2004.
    [6]周慧,王晓光.基于BP神经网络的中国火灾灰色回归组合预测模型[J].统计与决策,2008(14):39-41.
    [7]常宁.基于BP神经网络的人口火灾发生率预测方法研究[J].中国人民公安大学学报,2013(4):69-71.
    [8]辛晶,夏登友,康青春,等.BP神经网络技术在交通工具火灾预警中的应用[J].中国安全科学学报,2006,16(11):29-33.
    [9]Tomoski Nishino,Takeyoshi Tanaka,Akihiko Hokugo.An Evaluation Method for the Urban Post-earthquake Fire Risk Considering Multiple Scwnarios of Fire Spread and Evacuation[J].Fire Saftey Journal,2012,54:167-180.
    [10]钟江荣.城市地震次生火灾研究[D].哈尔滨:中国地震局工程力学研究所,2010.
    [11]张肇诚.中国震例(1966-1975,1976-1980,1986-1988,1992-1994)[M].北京:地震出版社,2002.
    [12]周品.MATLAB神经网络设计与应用[M].北京:清华大学出版社,2013.
    [13]尹绍飞,苏勇.BP神经网络在股指预测中的应用[J].科学技术与工程,2009,9(24):153-184.
    [14]董长虹.MATLAB神经网络设计与应用[M].北京:国防工业出版社,2007.
    [15]徐冠,夏克文,徐乃勋.基于LM算法的神经网络在冠心病诊断中的应用[J].微电子学与计算机,2006,23(2):189-192.
    [16]巨林仓,史贝贝,杨清宇,等.基于LM算法建立风电机组神经网络故障预警诊断模型[J].热力发电,2010,39(12):44-49.
    [17]张晓达,李黎,肖建华,等.武汉市抗震防灾规划(2010—2020)说明书[M].武汉:武汉市城乡建设委员会,2010.
    [18]张晓达,魏文晖,李黎.武汉市抗震防灾规划(2009—2020)次生灾害防御专题研究报告[R].武汉:武汉市城乡建设委员会,2010.

版权所有:© 2023 中国地质图书馆 中国地质调查局地学文献中心