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| 1 | 基于粗糙集优化支持向量机的泥石流危险度预测模型显示文摘为准确预测泥石流危险度,提出了基于粗糙集理论(rough set,RS)的粒子群算法(particle swarm optimization,PSD)优化支持向量机(support vector machine,SVM)模型。首先离散化泥石流样本数据形成初始决策表,利用粗糙集理论对10个泥石流危险度影响指标进行属性约简,将约简后的泥石流指标数据归一化处理作为支持向量机的学习样本,通过粒子群算法寻优获得最佳支持向量机模型参数,最终建立基于粗糙集的泥石流危险度预测的优化支持向量机模型。并将构建的RS-PSO-SVM模型用于对测试样本的预测。结果表明:在相同训练样本的条件下,RS-PSO-SVM模型、PSO-SVM模型及RS-PSO-BP模型三者的预测准确率分别为87.5%、87.5%、75%,说明RS-PSO-SVM模型和PSO-SVM模型具有比RS-PSO-BP模型更高的精度。此外,尽管RS-PSO-SVM模型和PSO-SVM模型具有相同的预测精度,但是由于进行了属性约简,RS-PSO-SVM模型可以有效提高运行效率,降低模型复杂度。 | 王晨晖 袁颖 周爱红 刘立申 王利兵 陈凯南 | 2019 | 科学技术与工程2019，19，31： | 7 |
| 2 | 基于Flow-R模型的八一沟泥石流危险性评价显示文摘目前泥石流危险性评价方法通常是一条泥石流沟对应一个危险等级。Flow-R模型将泥石流源区识别与泥石流运动相结合计算泥石流的危险概率,能够评价一条泥石流沟内不同部位的危险性。为丰富泥石流评价方法的应用研究及探究单沟内泥石流危险分布特征,以八一沟为研究区,在确定八一沟泥石流源区识别阈值和运动参数的基础上,用Flow-R模型对泥石流可能的危害范围进行模拟计算,并用混淆矩阵对模拟结果进行评估,最后对八一沟流域不同部位进行了泥石流危险性评价。结果表明:(1)泥石流源区主要分布于沟道20°~50°坡度范围和1 400~1 600 m高程范围内,沟顶细小汇水沟道为泥石流提供了丰富的活动物质;(2)泥石流危险区域大致分布在沟道左右40 m范围,占整个研究区域的20.06%;极高危险区分布于沟道中心,危险性由沟道中心向两边逐渐降低;(3)Flow-R应用于研究区的正确率为84.18%,给出的泥石流危险区图合理,能够反映研究区泥石流的基本危险特征。 | 聂银瓶 李秀珍 | 2019 | 自然灾害学报2019，0，1： | 6 |
| 3 | Valuation of debris flow mitigation measures in tourist towns:a case study on Hongchun gully in southwest China显示文摘The estimation of the value on the engineering project in tourist towns is usually very challenging and controversial. In this study, an attempt has been made to evaluate the economic value of the debris flow control engineering in tourist towns by integrating both welfare and disaster economics. The total value of debris flow prevention and control engineering in tourist towns(VDFE) includes investment cost(IC), disaster mitigation benefit(DMB), and loss of brand value(LBV). Here DMB is assessed by the cost-benefit method. The LBV is estimated by incorporating brand equity and costbenefit methods. The engineering for debris flow control in the Hongchun Gully of southwest China was built to protect Yingxiu tourist town and was assessed as an example. The IC for the engineering is180 million RMB, however, the VDFE reaches as high as 3401 million RMB, of which the LBV is 169 million RMB, and the input-output ratio is 1:18. Thus, the LBV cannot be neglected in case of VDFE estimation process. The more developed the tourism in one town or city is, the greater the LBV and the higher the VDFE are. | CHEN Ming-li HU Gui-sheng CHEN Ning-sheng ZHAO Cun-yao ZHAO Song-jiang HAN Da-wei | 2016 | Journal of Mountain Science2016，13，10： | 2 |
| 4 | 基于三参Weibull分布的泥石流降雨动态预警模型显示文摘降雨是触发泥石流灾害的重要因素。现有的泥石流预警模型多为半定量的预警,通过划分不同的预警级别来预报灾情,没有做到任意时刻泥石流爆发的定量计算。通过分析文家沟5次大型泥石流灾害的降雨数据,引入泥石流爆发降雨驱动指标RTI并运用三参Weibull分布确定了绵竹市清平镇文家沟泥石流的降雨阈值,提出了计算任意雨量下的泥石流的瞬时发生概率。最后通过Weibull分布结果和泥石流堆积方量的计算值拟合出文家沟泥石流爆发概率和堆积方量的关系。该模型不仅实现了文家沟泥石流灾害的动态定量预警,同时也给出了任意概率下泥石流堆积方量的域值区间。最后以2012.8.13文家沟泥石流事件为例验证了该模型,说明三参Weibull分布可以用于泥石流分析并建立预警模型,可将此法推广到其他地质灾害的分析及预警中。 | 魏兰婷 许强 杨琴 | 2015 | 科学技术与工程2015，35，34： | 1 |
| 5 | SIRENE: A Spatial Data Infrastructure to Enhance Communities' Resilience to Disaster-Related Emergency显示文摘Planning in advance to prepare for and respond to a natural hazard-induced disaster-related emergency is a key action that allows decision makers to mitigate unexpected impacts and potential damage. To further this aim, a collaborative, modular, and information and communications technology-based Spatial Data Infrastructure(SDI)called SIRENE—Sistema Informativo per la Preparazione e la Risposta alle Emergenze(Information System for Emergency Preparedness and Response) is designed and implemented to access and share, over the Internet, relevant multisource and distributed geospatial data to support decision makers in reducing disaster risks. SIRENE flexibly searches and retrieves strategic information from local and/or remote repositories to cope with different emergency phases. The system collects, queries, and analyzes geographic information provided voluntarily by observers directly in the field(volunteered geographic information(VGI) reports) to identify potentially critical environmental conditions. SIRENE can visualize and cross-validate institutional and research-based data against VGI reports,as well as provide disaster managers with a decision support system able to suggest the mode and timing of intervention, before and in the aftermath of different types of emergencies, on the basis of the available information and in agreement with the laws in force at the national andregional levels. Testing installations of SIRENE have been deployed in 18 hilly or mountain municipalities(12 located in the Italian Central Alps of northern Italy, and six in the Umbria region of central Italy), which have been affected by natural hazard-induced disasters over the past years(landslides, debris flows, floods, and wildfire) and experienced significant social and economic losses. | Simone Sterlacchini Gloria Bordogna Giacomo Cappellini Debora Voltolina | 2018 | International Journal of Disaster Risk Science2018，9，1： | 1 |
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