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相关概念视频

End Point Prediction: Gran Plot01:07

End Point Prediction: Gran Plot

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A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
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Applications of GIS: Disaster Management and Emergency Response01:29

Applications of GIS: Disaster Management and Emergency Response

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Geographic Information System (GIS) technology is essential for risk identification, action prioritization, and resource optimization in critical situations like flooding and earthquakes. By integrating spatial and demographic data, GIS provides a comprehensive framework for emergency response.GIS integrates data layers, like rainfall intensity, topography, elevation profiles, and river levels, to model high-risk flood zones. These layers assess areas susceptible to flooding based on their...
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Global Climate Change01:50

Global Climate Change

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Throughout its ~4.5 billion year history, the Earth has experienced periods of warming and cooling. However, the current drastic increase in global temperatures is well outside of the Earth’s cyclic norms, and evidence for human-caused global climate change is compelling. Paleoclimatology, the study of ancient climate conditions, provides ample evidence for human-caused global climate change by comparing recent conditions with those in the past.
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Survival Tree01:19

Survival Tree

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Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
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Prediction Intervals01:03

Prediction Intervals

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The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
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Elastic Collisions: Case Study

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Elastic collision of a system demands conservation of both momentum and kinetic energy. To solve problems involving one-dimensional elastic collisions between two objects, the equations for conservation of momentum and conservation of internal kinetic energy can be used. For the two objects, the sum of momentum before the collision equals the total momentum after the collision. An elastic collision conserves internal kinetic energy, and so the sum of kinetic energies before the collision equals...
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相关实验视频

Updated: Sep 19, 2025

Measuring and Mapping Patterns of Soil Erosion and Deposition Related to Soil Carbonate Concentrations Under Agricultural Management
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Published on: September 12, 2017

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深度学习可以预测全球地震引发的山体滑坡.

Xuanmei Fan1, Xin Wang1, Chengyong Fang1

  • 1State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China.

National science review
|June 16, 2025
PubMed
概括
此摘要是机器生成的。

科学家们创建了一个全球山体滑坡数据库,并使用深度学习来预测全球地震引发的山体滑坡. 该工具提供快速,准确的危险评估,改善灾害应对和规划.

关键词:
深度学习是一种深度学习.地震引发的山体滑坡是地震引发的全球数据库全球数据库滑坡预测模型的模型

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Data Processing Methods for 3D Seismic Imaging of Subsurface Volcanoes: Applications to the Tarim Flood Basalt
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Data Processing Methods for 3D Seismic Imaging of Subsurface Volcanoes: Applications to the Tarim Flood Basalt

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相关实验视频

Last Updated: Sep 19, 2025

Measuring and Mapping Patterns of Soil Erosion and Deposition Related to Soil Carbonate Concentrations Under Agricultural Management
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Data Processing Methods for 3D Seismic Imaging of Subsurface Volcanoes: Applications to the Tarim Flood Basalt
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科学领域:

  • 地质科学 地质科学
  • 地理危险 地区性危险
  • 计算地震学计算地震学

背景情况:

  • 地震引发的山体滑坡是一个主要的致命危险,需要迅速应对,以防止连续发生的灾难.
  • 目前的预测方法受到简化的模型,有限的区域数据和回顾性分析的阻碍,阻碍了及时的危险评估.
  • 有效地质危险预测需要全面的全球数据和先进的分析技术.

研究的目的:

  • 开发一个全面的全球地震引发的山体滑坡数据库.
  • 创建先进的深度学习模型,以快速,准确地预测地震后的山体滑坡概率.
  • 为即时灾难评估和事前危险规划提供一个可扩展的工具.

主要方法:

  • 编制了一个全球数据库,记录了过去50年来38次大地震造成的约40万次山体滑坡.
  • 开发并应用先进的深度学习模型来预测山体滑坡概率.
  • 已验证的模型性能,用于快速的全球危险评估.

主要成果:

  • 在山体滑坡预测中达到约82%的平均空间准确度.
  • 在不到一分钟的时间内预测任何全球地震的山体滑坡概率.
  • 在危险评估中成功绕过了先前当地知识的需求.

结论:

  • 开发的框架为全球地缘危险预测提供了转型性的进步.
  • 能够快速评估灾害,并加强地震引发的山体滑坡的事前危险规划.
  • 提供了一个可扩展和有效的工具,以减轻地震滑坡的灾难性影响.