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相关概念视频

Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

42
Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
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Selected Data About Geographic Locations01:25

Selected Data About Geographic Locations

27
Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
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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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Manipulation and Analysis01:21

Manipulation and Analysis

23
GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
23
Survival Tree01:19

Survival Tree

75
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.
 Building a Survival Tree
Constructing a...
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Response Surface Methodology01:16

Response Surface Methodology

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Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
110

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相关实验视频

Updated: Jun 19, 2025

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
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开发一个过境沙漠交互式仪表板:监督建模用于预测过境沙漠.

Seung Jun Choi1, Junfeng Jiao1

  • 1Urban Information Lab, The School of Architecture, The University of Texas at Austin, Austin, TX, United States of America.

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概括
此摘要是机器生成的。

这项研究使用机器学习来识别过境沙漠,发现密度和设计是关键因素. 解决方案包括减少密度和增加绿色空间,重点关注性别特定的运输需求.

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Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon
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科学领域:

  • 城市规划 城市规划
  • 运输科学 运输科学
  • 数据科学数据科学数据科学

背景情况:

  • 过境沙漠,公共交通不足的地区,不成比例地影响某些人口.
  • 了解导致过境沙漠的因素对于公平的城市发展至关重要.

研究的目的:

  • 使用机器学习框架识别导致过境沙漠的因素.
  • 提出可行的解决方案,将过境沙漠转化为过境绿洲.
  • 分析运输需求,考虑到高峰时段的性别差异.

主要方法:

  • 采用了多类监督机器学习框架,评估了支持矢量机,决策树,随机森林和K-最近邻近算法.
  • 选择了随机森林模型,并通过多元反事实解释和夏普利添加式解释进行了深入分析.
  • 排列特征的重要性,揭示密度,设计,运输距离,建筑环境多样性和社会人口统计作为重要因素.

主要成果:

  • 导致过境沙漠的关键因素包括人口密度,交通便利性和城市设计.
  • 不同的反事实解释表明,减少人口密度和增加绿色空间可以缓解过境沙漠.
  • 沙普利的附加解释揭示了各种过境沙漠特征的差异性影响,突出了性别特定的过境需求,特别是女性.

结论:

  • 过境沙漠的识别和解决方案受到数据聚合和人口分离的影响,特别是按性别.
  • 解决过境沙漠问题需要优先考虑弱势群体,改善过境设计和可访问性.
  • 机器学习模型,交互式仪表板和参与式规划可以推进公平的交通解决方案.