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相关概念视频

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

81
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...
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Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

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Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
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Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

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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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Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

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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...
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Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

675
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
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Response Surface Methodology01:16

Response Surface Methodology

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Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
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Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
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基于多目标狮女优化算法和系统动态模型的城市人口预测.

Dong Li1, Yanyan Yu2, Bo Wang1

  • 1School of Economics and Management, Xi'an University of Posts and Telecommunications, Xi'an, 710061, China.

Scientific reports
|July 22, 2023
PubMed
概括
此摘要是机器生成的。

城市人口预测对于发展至关重要. 结合狮子女优化和系统动态的新模型预测西安的人口,确定就业和出生政策是关键的增长驱动力.

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科学领域:

  • 城市规划是城市规划.
  • 人口统计学 人口统计学
  • 计算建模计算建模

背景情况:

  • 人口规模与经济和社会发展密切相关.
  • 科学的人口预测对于有效的城市发展战略至关重要.

研究的目的:

  • 开发和验证一个城市人口预测模型.
  • 预测2019年至2050年西安的人口趋势.
  • 分析各种政策对未来人口动态的影响.

主要方法:

  • 一种混合模型,将多目标狮女优化算法与系统动态集成在一起.
  • 优化关键系统动态参数以提高模型的客观性.
  • 在三个场景中模拟了五个政策因素 (出生,就业,科技,医疗保健,教育).

主要成果:

  • 该模型准确地预测了2019年至2050年的西安人口.
  • 西安的人口预计在2040年达到147,939,242人.
  • 就业和生育政策对人口规模产生了最显著的积极影响,其次是教育,科技和卫生政策.

结论:

  • 就业和出生政策是人口增长最有效的杆.
  • 所有五个分析的政策的协调实施提供了人口增长的最快途径.
  • 开发的模型为科学城市人口战略制定提供了一个强大的工具.