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选取2013年松原5.8级震群23个MS≥3.0地震事件,通过地震波的振动持续时间、速度、周期、振幅等,进行震相识别,综合分析发现:该区域土层较厚,且震源相对较浅,面波较发育,波列的振动持续时间较长;地震震相主要以Pn、Sn、Pg、Sg、PmP、SmS为主:其中PmP、SmS震相在震中距70—110 km范围内较易识别;Pn、Sn震相在震中距150 km以上可较清晰的识别,随着震中距增大,Sn震相在震中距350 km以上将不易识别。 相似文献
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Rainfall prediction is of vital importance in water resources management. Accurate long-term rainfall prediction remains an open and challenging problem. Machine learning techniques, as an increasingly popular approach, provide an attractive alternative to traditional methods. The main objective of this study was to improve the prediction accuracy of machine learning-based methods for monthly rainfall, and to improve the understanding of the role of large-scale climatic variables and local meteorological variables in rainfall prediction. One regression model autoregressive integrated moving average model (ARIMA) and five state-of-the-art machine learning algorithms, including artificial neural networks, support vector machine, random forest (RF), gradient boosting regression, and dual-stage attention-based recurrent neural network, were implemented for monthly rainfall prediction over 25 stations in the East China region. The results showed that the ML models outperformed ARIMA model, and RF relatively outperformed other models. Local meteorological variables, humidity, and sunshine duration, were the most important predictors in improving prediction accuracy. 4-month lagged Western North Pacific Monsoon had higher importance than other large-scale climatic variables. The overall output of rainfall prediction was scalable and could be readily generalized to other regions. 相似文献
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Based on raw data from dams damaged in the Wenchuan earthquake, including many that were severely damaged, characteristics and factors that influenced the damage are discussed in this paper. Findings from this study include: severely damaged dams were densely distributed along the seismologic fault; small dams, especially small earth-rock dams, had the most serious damage that was caused by a variety of factors; the most serious damage was caused by seismic waves; damage was aggregated by aftershocks; and the extent of the damage patterns increased with the seismic intensity. Damage patterns varied in different intensity zones and cracking was the most common type of damage. Most of the dams had a good base with relatively high bearing capacity, and the walls of the earth-rock dams were mostly of clay soil. This type of base and body material mitigated some of the damage to dams. Reservoir maintenance and other factors also have a significant impact on the seismic safety of the dam. Finally, some recommendations to reduce seismic damage to dams are proposed. 相似文献
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物源问题的研究对于了解和确定研究区有利沉积相带及储集砂体的分布、寻找有利油气储集层具有重要意义。胜坨地区沙四上勘探程度相对较低,前人关于目的层段的物源体系的研究成果很少。为了进一步查清研究区沙四上沉积时期砂体成因和物源方向,更好地预测砂体的分布,本文综合运用地震、测井、地球化学等资料,采用古地貌分析法、沉积砂体岩屑类型对比法、砂岩百分含量法和沉积物特征元素等方法探讨了胜坨地区沙四上亚段砂体的物源方向,并结合特征元素物源指数判别公式对沙四上亚段物源体系实现了定量评价。综合分析认为研究区沙四上亚段具有多物源体系特征,除了直接来自于胜北断层和坨94断层上升盘的物源外,还有沿着胜北断层与坨94断层转换带处的物源体系。 相似文献