简化方法用于确定修改后的科斯蒂亚科夫模型参数的分析
1School of Technology, MANUU, Hyderabad 500032, India
概括
准确的透率估计对于水文项目至关重要. 修改后的科斯蒂亚科夫模型的简化方法被发现比非线性优化不那么可靠,减少了72%的误差.
科学领域:
- 水文学的水文学
- 土壤科学 土壤科学
- 水资源管理 水资源管理
背景情况:
- 对水文工程项目来说,准确估计透损失至关重要,但由于数据稀缺,往往需要实证模型.
- 科斯蒂亚科夫模型是一种常见的透模型,但需要修改以考虑初始的零透.
- 最近提出了一种简化方法,用于修改后的科斯蒂亚科夫模型中的参数确定.
研究的目的:
- 分析一种简化方法的可靠性,用于确定修改后的Kostiakov透模型的参数.
- 用现实数据比较简化方法与非线性优化方法的性能.
主要方法:
- 来自全球不同地区的六个观察到的透数据集的分析.
- 从简化方法获得的累积透估计的比较与非线性优化解决方案 (基于Excel).
- 使用二次错误总和指标对模型性能进行评估.
主要成果:
- 在修改后的科斯蒂亚科夫模型中,简化的参数确定方法显示了精度的局限性.
- 非线性优化在估计累积透时显著超过了简化方法.
- 与简化方法相比,使用非线性优化时,二次错误总和平均减少了72%.
结论:
- 修改的科斯蒂亚科夫模型参数化的简化方法对于准确的透估计来说不那么可靠.
- 非线性优化为确定修改后的科斯蒂亚科夫模型参数提供了更强大,更准确的方法.
- 水文学家应考虑先进的优化技术,以改善项目中的透损失估计.
相关概念视频
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
515
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
On...
515
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
56
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
56
Mechanistic Models: Compartment Models in Individual and Population Analysis
43
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...
43
Linear Approximation in Time Domain
83
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
83
Linear Approximation in Frequency Domain
91
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
91
Routh-Hurwitz Criterion II
254
In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first...
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first...
254


