Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

106
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
106
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

139
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
139
Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

46
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...
46
End Point Prediction: Gran Plot01:07

End Point Prediction: Gran Plot

318
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...
318
Extraction: Advanced Methods00:56

Extraction: Advanced Methods

446
Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
446
Modeling and Similitude01:12

Modeling and Similitude

266
Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
266

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

A national-scale dataset for neighbourhood-level urban building energy modelling for England and Wales.

Scientific data·2026
Same author

Responsible Artificial Intelligence for Earth observation: human rights and the EU AI act.

AI and ethics·2026
Same author

Deciphering exterior: building energy efficiency prediction with emerging urban big data.

npj urban sustainability·2026
Same author

The influence of city size versus urban form on land surface temperature variation and the surface urban heat island effect: A cross-city analysis of German cities.

PloS one·2026
Same author

Heatwave increases nighttime light intensity in hyperdense cities of the Global South: a double machine learning study.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2025
Same author

Heat stress dichotomy: long-term adaptation and acute shock in London domestic environments.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2025
Same journal

Novel Parent Survey Measures Sensory Behaviors Incorporating Sensory Modality and Stimulus Intensity.

Heliyon·2026
Same journal

Expression of concern: "SQSTM1/p62 promotes the progression of gastric cancer through epithelial-mesenchymal transition" [Heliyon 10 (2024) e24409].

Heliyon·2026
Same journal

Expression of concern: "TL1A promotes metastasis and EMT process of colorectal cancer" [Heliyon 10 (2024) e24392].

Heliyon·2026
Same journal

Expression of concern: "Factors affecting timing of surgery following neoadjuvant chemoradiation for esophageal cancer" [Heliyon 9 (2023) e23212].

Heliyon·2026
Same journal

Expression of concern: "On stratified single-valued soft topogenous structures" [Heliyon 10 (2024) e27926].

Heliyon·2026
Same journal

Expression of concern: "Artifact removal and motor imagery classification in EEG using advanced algorithms and modified DNN" [Heliyon 10 (2024) e27198].

Heliyon·2026
查看所有相关文章

相关实验视频

Updated: Jun 29, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.0K

城市扩张模拟与一个可解释的集体深度学习框架.

Yue Zhu1,2, Christian Geiß3, Emily So2

  • 1Swiss Federal Institute of Technology, ETH Zurich, Department of Civil, Environmental and Geomatic Engineering, Institute of Environmental Engineering, Hydrology and Water Resources Management, Laura-Hezner-Weg 7, 8093, Zurich, Switzerland.

Heliyon
|April 8, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了一个新的深度学习框架,以高精度模拟城市扩张. 该模型增强了可解释性,提高了对城市土地动态预测的信心,以改善土地管理.

关键词:
深度学习是一种深度学习.整合框架 整合框架机器学习 机器学习空间建模 空间建模城市扩建模拟

更多相关视频

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

529
A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
05:41

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

9.4K

相关实验视频

Last Updated: Jun 29, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.0K
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

529
A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
05:41

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

9.4K

科学领域:

  • 城市和区域规划 城市和区域规划
  • 地理信息科学 地理信息科学
  • 人工智能的人工智能

背景情况:

  • 城市扩张模拟对于有效的土地管理和政策制定至关重要.
  • 深度学习的进步为预测城市土地动态提供了更高的准确性.
  • 现有的方法在解释性和城市内颗粒模拟方面面临挑战.

研究的目的:

  • 提出一种基于深度学习的全新整体框架,用于城市内颗粒式城市扩张模拟.
  • 提高深度学习模型在空间分析中的可解释性.
  • 提高城市扩张预测的准确性和时间一致性.

主要方法:

  • 开发了一个集体框架,利用变压器用于多时空空间特征和卷积层用于单时空特征.
  • 集成了一个通道智能的注意模块来评估特征重要性和模型可解释性.
  • 应用框架来模拟中国深的城市扩张.

主要成果:

  • 拟议的深度学习框架准确地模拟了城市内部城市水平的城市扩张.
  • 道智能的注意模块提高了对模拟结果的解释性和信心.
  • 该方法在空间准确性和时间一致性方面都超过了基线方法.

结论:

  • 新的深度学习整体框架为城市扩张模拟提供了强大的和可解释的解决方案.
  • 这种方法为加强土地管理和城市政策制定提供了巨大的潜力.
  • 通过先进的深度学习技术,可以实现准确的城市内规模预测.