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暴雨洪水诱发地下钨矿灾害链式演化及风险分析
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作者 邵彦斌 陈尚波 +3 位作者 王清和 刘珮勋 虞松涛 李佳 《有色金属科学与工程》 CAS 2024年第5期750-757,共8页
暴雨洪水常导致矿山发生一系列灾害,造成重大损失和影响。本文通过分析暴雨洪水诱发地下钨矿山灾害链式演化及风险特征,识别其中灾害事件,建立灾害链式演化模型;基于复杂网络理论构建了含47个节点和176条边的灾害网络模型,随后分析节点... 暴雨洪水常导致矿山发生一系列灾害,造成重大损失和影响。本文通过分析暴雨洪水诱发地下钨矿山灾害链式演化及风险特征,识别其中灾害事件,建立灾害链式演化模型;基于复杂网络理论构建了含47个节点和176条边的灾害网络模型,随后分析节点度值、节点子网数、边脆弱性等参数,识别了灾害网络的关键点和关键边。结果表明:淹井、厂房冲毁、工业场地浸水、工业场地掩埋和工业场地破坏的重要度分别是0.3283、0.1154、0.1099、0.0845和0.0845,是灾害网络的关键节点;地表水→地表径流、地表径流→泥石流、矿井突涌水→淹井、地表径流→崩塌滑坡和地表径流→山洪的边脆弱性分别是373.7151、354.7824、346.1536、336.1222和335.8385,是灾害网络的关键边,据此提出了断链减灾建议。研究结果可为暴雨洪水诱发地下钨矿灾害防治提供科学依据。 展开更多
关键词 钨矿山 灾害 灾害网络模型 关键节点 关键边
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Storm surge disaster evaluation model based on an artificial neural network 被引量:1
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作者 纪芳 侯一筠 《Chinese Journal of Oceanology and Limnology》 SCIE CAS CSCD 2011年第5期1142-1146,共5页
Back propagation is employed to forecast the current of a storm with various characteristics of storm surge; the technique is thus important in disaster forecasting. One of the most fuzzy types of information in the p... Back propagation is employed to forecast the current of a storm with various characteristics of storm surge; the technique is thus important in disaster forecasting. One of the most fuzzy types of information in the prediction of geological calamity is handled employing the information diffusion method. First, a single-step prediction model and neural network prediction model are employed to collect influential information used to predict the extreme tide level. Second, information is obtained using the information diffusion method, which improves the precision of risk recognition when there is insufficient information. Experiments demonstrate that the method proposed in this paper is simple and effective and provides better forecast results than other methods. Future work will focus on a more precise forecast model. 展开更多
关键词 storm surge information diffusion neural network prediction model extreme tide level risk recognition
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Research on Risk Assessment of City Natural Disaster based on Neural Network
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作者 Xinyan WU 《International Journal of Technology Management》 2014年第7期109-111,共3页
Aiming at the selection of fuzzy AHP and fuzzy DH methods in the previous studies, this paper evaluate the qualitative index system using expert questionnaire, the self-learning BP neural network model to construct th... Aiming at the selection of fuzzy AHP and fuzzy DH methods in the previous studies, this paper evaluate the qualitative index system using expert questionnaire, the self-learning BP neural network model to construct the index of system, and complete the establishment of model, in order to avoid the serious subjectivity, and using statistical and measurement methods test the reliability index, analyze the validity of the evaluation index system and completeness. Finally, the paper validate the practicability of the model. 展开更多
关键词 Geological disaster disaster prevention and mitigation neural network risk assessment
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