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相关概念视频

Instrument Calibration01:12

Instrument Calibration

208
Instrument calibration is essential for ensuring that instruments produce accurate and consistent results. It is vital in manufacturing, healthcare, testing laboratories, and scientific research. Calibration processes are specific to each instrument and help enhance data accuracy. Each instrument has a unique calibration process tailored to its design and function to improve data accuracy.
Analytical Balance Calibration
An analytical balance measures mass and requires regular calibration to...
208
Testing Water Quality01:14

Testing Water Quality

121
When the quality of water for concrete preparation is uncertain, its impact on the setting time of cement and compressive strength of mortar is assessed by comparison with de-ionized or distilled water benchmarks. American Society for Testing and Materials (ASTM) C1602 requires the setting times to be within 90 minutes of the control, British Standard (BS) 3146:1980 allows a 30-minute variance in the initial setting, while British Standards European Norm (BS EN) 1008 specifies initial setting...
121
Typical Model Studies01:30

Typical Model Studies

367
Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
367
Calibration Curves: Linear Least Squares01:20

Calibration Curves: Linear Least Squares

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A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
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Quality of Water01:19

Quality of Water

108
In concrete preparation, the quality of water is paramount as it affects the strength and durability of the concrete. Potable water is usually preferred; however, it must not have excessive sodium or potassium to prevent compromising the concrete's integrity. Water quality is typically evaluated based on impurities such as dissolved solids, chlorides, and sulfates, and its pH value is ideally between 6 and 8. Even slightly acidic natural water may be acceptable unless it contains harmful...
108
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

62
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
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相关实验视频

Updated: Jul 14, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework
12:44

Watershed Planning within a Quantitative Scenario Analysis Framework

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对于水质模型参数的贝叶斯式校准.

Bing Bai1,2, Fei Dong1,2, Wenqi Peng1,2

  • 1State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing, China.

Water environment research : a research publication of the Water Environment Federation
|October 9, 2023
PubMed
概括
此摘要是机器生成的。

本研究引入了贝叶斯的水质模型校准方法,提高了准确性和效率. 马尔科夫链蒙特卡洛算法优化参数估计,实现平均相对误差低于10%.

关键词:
贝叶斯的推理 贝叶斯的推理马尔科夫连锁蒙特卡罗的蒙特卡罗是一个对参数进行校准.水质模型的水质模型.

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Last Updated: Jul 14, 2025

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科学领域:

  • 环境科学 环境科学
  • 水质建模水质建模
  • 计算水文学计算水文学

背景情况:

  • 传统的水质模型校准方法往往与局部最佳值和参数等效性作斗争,限制了准确性和效率.
  • 准确的参数校准对于可靠的水质预测和有效的环境管理至关重要.

研究的目的:

  • 提出一种基于贝叶斯的新方法,用于水质模型参数校准.
  • 为了提高校准效率和准确性,避免局部最佳值和参数等效.
  • 为了提高校准过程的收速度.

主要方法:

  • 参数校准问题被重新定义为后置概率函数抽样问题.
  • 贝叶斯推断和马尔科夫链蒙特卡洛 (MCMC) 算法用于采样.
  • 设置了优化的初始采样值,以提高MCMC的收速度.

主要成果:

  • 拟议的贝叶斯方法实现了参数校准的平均相对误差 (MRE) 低于10%.
  • 对Dx和Dy的特定MREs分别为5.3%和8.3%.
  • 通过优化初始MCMC值,马尔科夫链长度和提案分布,提高了校准效率.

结论:

  • 基于贝叶斯的方法为水质模型参数校准提供了一种高效和准确的方法.
  • 优化的MCMC初始值显著提高了校准效率.
  • 该方法在各种水质模型中显示了广泛的适用性.