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相关概念视频

Regression Analysis01:11

Regression Analysis

6.1K
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:
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Temperature Measurement Sites01:14

Temperature Measurement Sites

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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...
2.3K
Random Error01:04

Random Error

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Random or indeterminate errors originate from various uncontrollable variables, such as variations in environmental conditions, instrument imperfections, or the inherent variability of the phenomena being measured. Usually, these errors cannot be predicted, estimated, or characterized because their direction and magnitude often vary in magnitude and direction even during consecutive measurements. As a result, they are difficult to eliminate. However, the aggregate effect of these errors can be...
1.8K
Multiple Regression01:25

Multiple Regression

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Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
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Assessing Body Temperature - Temporal Artery01:19

Assessing Body Temperature - Temporal Artery

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Here is a stepwise guide to assessing the body temperature at the temporal artery using a temporal artery thermometer
Step 1: Perform hand hygiene and don a fresh pair of gloves to prevent cross-infection and ensure patient safety.
Step 2: Explain the procedure to the patient to establish trust. Clear communication establishes trust with the patient, ensures they understand what to expect, promotes cooperation, and enhances comfort during the procedure.  
Step 3: Assess the patient's...
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Heating and Cooling Curves02:44

Heating and Cooling Curves

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When a substance—isolated from its environment—is subjected to heat changes, corresponding changes in temperature and phase of the substance is observed; this is graphically represented by heating and cooling curves.
For instance, the addition of heat raises the temperature of a solid; the amount of heat absorbed depends on the heat capacity of the solid (q = mcsolidΔT). According to thermochemistry, the relation between the amount of heat absorbed or released by a substance, q, and its...
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相关实验视频

Updated: Sep 18, 2025

Author Spotlight: Simulation and Analysis of the Temperature Rise of Ring Main Unit Equipment
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使用基于埃及最佳子集回归模型的数据驱动技术进行空气温度估计和建模.

Ahmed Elbeltagi1, Dinesh Kumar Vishwakarma2, Okan Mert Katipoğlu3

  • 1Agricultural Engineering Department, Faculty of Agriculture, Mansoura University, Mansoura, 35516, Egypt. ahmedelbeltagy81@mans.edu.eg.

Scientific reports
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PubMed
概括
此摘要是机器生成的。

机器学习模型M5 pruned (M5P) 准确预测半干旱地区每日最低和最高气温. 这项研究确定M5P是改善水资源管理和农业规划的卓越模式.

关键词:
输入选择输入选择机器学习 机器学习回归分析是一种回归分析.预测温度 预测温度

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相关实验视频

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Surface Renewal: An Advanced Micrometeorological Method for Measuring and Processing Field-Scale Energy Flux Density Data
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科学领域:

  • 环境科学 环境科学
  • 农业科学 农业科学
  • 数据科学数据科学数据科学

背景情况:

  • 准确的空气温度预测对于水资源管理,水文研究和气候变化影响评估至关重要.
  • 半干旱地区在供水方面面临着独特的挑战,因此精确的温度预测对于农业规划和可持续性至关重要.

研究的目的:

  • 确定最准确的机器学习模型,用于预测半干旱环境中的每日最低 (Tmin) 和最高 (Tmax) 空气温度.
  • 为了比较线性回归 (LR),增量回归 (AR),支向量机 (SVM),随机子空间 (RSS) 和M5修剪 (M5P) 模型的性能.

主要方法:

  • 利用埃及加尔比亚省的历史每日温度数据 (1979-2014),分为75%的训练和25%的测试集.
  • 应用最佳子集回归来确定Tmin和Tmax预测的最佳输入变量组合.
  • 评估了五种基于根平均平方误差 (RMSE),平均绝对误差 (MAE),相对绝对误差 (RAE),纳什-萨特克利夫效率 (NSE) 和皮尔森相关系数 (PCC) 的机器学习模型.

主要成果:

  • 与LR,AR,RSS和SVM相比,M5修剪 (M5P) 模型在预测Tmax和Tmin方面表现优异.
  • M5P获得了最低的RMSE (2.4881°C为Tmin,2.7696°C为Tmax) 和MAE,以及最高的NSE (0.8048为Tmin,0.8720为Tmax).
  • 统计测试 (弗里德曼ANOVA,Dunn的测试) 证实了模型之间的显著差异,M5P和RSS显示高变化和SVM显著不同.

结论:

  • M5 pruned (M5P) 模型是一个强大的,准确的工具,用于在半干旱地区每天预测空气温度.
  • 这些发现为提高水资源管理,灌和农业生产率的决策提供了宝贵的见解.
  • 实施M5P可以提高运营效率,促进脆弱的半干旱环境中的可持续性.