Jove
Visualize
联系我们

相关概念视频

Temperature Measurement Sites01:14

Temperature Measurement Sites

1.4K
A thermometer measures body temperature. The common sites for measuring body temperature are the oral cavity, axillary region, temporal artery, and skin surface, such as the forehead, abdomen, and axilla. True core body temperature is assessed in the rectum, tympanic membrane, pulmonary artery, esophagus, and urinary bladder.
Oral: When assessing oral temperature, the thermometer tip should be placed under the tongue in the posterior sublingual pocket. It offers accurate readings and can be...
1.4K
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

89
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
89
Control Systems: Applications01:25

Control Systems: Applications

512
Electrical engineering plays a pivotal role in our daily lives, with control systems at the heart of many applications, from home appliances to sophisticated space shuttles. Control systems manage and regulate the behavior of devices and processes, ensuring they function safely, correctly, and efficiently.
In modern vehicles, control systems manage various functions to enhance performance and safety. The steering wheel and accelerator are primary inputs in a car's control system. The...
512
Regression Analysis01:11

Regression Analysis

5.4K
Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
5.4K
Thermometers and Temperature Scales01:22

Thermometers and Temperature Scales

4.9K
Any physical property that depends consistently and reproducibly on temperature can be used as the basis of a thermometer. For example, volume increases with temperature for most substances. This property is the basis for the common alcohol thermometer and the original mercury thermometers. Other properties used to measure temperature include electrical resistance, color, and the emission of infrared radiation.
As many physical properties depend on temperature, the variety of thermometers is...
4.9K
Quantifying Heat02:46

Quantifying Heat

53.2K
Thermal Energy 
53.2K

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

Retraction Note: Improving stroke risk prediction by integrating XGBoost, optimized principal component analysis, and explainable artificial intelligence.

BMC medical informatics and decision making·2026
Same author

TCN-QRNN model for short term energy consumption forecasting with increased accuracy and optimized computational efficiency.

Scientific reports·2025
Same author

Approach for enhancing the accuracy of semantic segmentation of chest X-ray images by edge detection and deep learning integration.

Frontiers in artificial intelligence·2025
Same author

Improving stroke risk prediction by integrating XGBoost, optimized principal component analysis, and explainable artificial intelligence.

BMC medical informatics and decision making·2025
Same author

An ensemble approach integrating LSTM and ARIMA models for enhanced financial market predictions.

Royal Society open science·2024
Same author

Author Correction: A novel hybrid supervised and unsupervised hierarchical ensemble for COVID-19 cases and mortality prediction.

Scientific reports·2024
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

相关实验视频

Updated: May 7, 2025

Author Spotlight: Simulation and Analysis of the Temperature Rise of Ring Main Unit Equipment
04:35

Author Spotlight: Simulation and Analysis of the Temperature Rise of Ring Main Unit Equipment

Published on: July 5, 2024

1.6K

创新的机器学习方法用于智能基础设施中的室内空气温度预测.

Nataliya Shakhovska1,2, Lesia Mochurad3, Rosana Caro4

  • 1Artificial Intelligence Department, Lviv Polytechnic National University, 12 S. Bandery St, Lviv, 79013, Ukraine. nataliya.b.shakhovska@lpnu.ua.

Scientific reports
|January 3, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种先进的长期短期记忆 (LSTM) 模型,具有滚动窗口交叉验证 (RWCV),用于准确的室内空气温度 (IAT) 预测,增强建筑能源管理和气候控制.

关键词:
累积错误分析 累积错误分析能源效率 能源效率是指能源的使用效率.这是LSTM的LSTM.机器学习是机器学习.智能建筑物 智能建筑物代理模拟代理模拟时间序列预测时间序列预测

更多相关视频

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

2.4K
In Situ Surface Temperature Measurement in a Conveyor Belt Furnace via Inline Infrared Thermography
07:03

In Situ Surface Temperature Measurement in a Conveyor Belt Furnace via Inline Infrared Thermography

Published on: May 30, 2020

4.3K

相关实验视频

Last Updated: May 7, 2025

Author Spotlight: Simulation and Analysis of the Temperature Rise of Ring Main Unit Equipment
04:35

Author Spotlight: Simulation and Analysis of the Temperature Rise of Ring Main Unit Equipment

Published on: July 5, 2024

1.6K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

2.4K
In Situ Surface Temperature Measurement in a Conveyor Belt Furnace via Inline Infrared Thermography
07:03

In Situ Surface Temperature Measurement in a Conveyor Belt Furnace via Inline Infrared Thermography

Published on: May 30, 2020

4.3K

科学领域:

  • 建筑科学 建筑科学
  • 机器学习 机器学习
  • 能源管理 能源管理

背景情况:

  • 高效的能源管理和保持最佳的室内气候对于现代建筑至关重要.
  • 准确预测室内空气温度 (IAT) 是实现这些目标的关键.
  • 传统的方法经常与建筑环境的动态性质作斗争.

研究的目的:

  • 通过机器学习提出一种用于IAT预测的创新代理建模方法.
  • 增强动态建筑数据的时间序列建模能力.
  • 提高温度预测的稳定性和通用性.

主要方法:

  • 长短期记忆 (LSTM) 网络的应用,用于时间序列分析.
  • 实施滚动窗口交叉验证 (RWCV) 以适应不断变化的数据趋势.
  • 开发一个全面的评估框架,包括MSE,R2和累积错误分析.

主要成果:

  • 拟议的LSTM与RWCV证明了强大的泛化,训练和测试数据集之间的损失差异最小.
  • 损失值从0.0004709到0.02819861不等,表明在不同的建筑条件下有效预测.
  • 对比分析显示,Adaboost和梯度提升在IAT预测中表现优于线性回归.

结论:

  • 与RWCV方法一起开发的LSTM对于建筑物中准确的IAT预测是有效的.
  • 该方法在动态时间序列数据方面,与传统的LSTM模型相比,提供了更好的适应性和稳定性.
  • 结果支持加强建筑气候管理,节能,并建议未来研究模式优化的途径.