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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

42
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...
42
Sampling Plans01:23

Sampling Plans

169
Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
169
Statically Indeterminate Problem Solving01:16

Statically Indeterminate Problem Solving

365
Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
365
Heuristics01:21

Heuristics

77
Heuristics are problem-solving strategies that use mental shortcuts to simplify decision-making. Unlike algorithms, which must be followed precisely to achieve a correct result, heuristics offer a general problem-solving framework. They save time and energy but can sometimes lead to less rational decisions.
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...
77
Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

40
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...
40
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

399
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...
399

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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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好的模式优化作为一个计划过程,使用一种新开发的优化算法.

Seyed Hayan Zaheri1, Mahdi Hosseini2, Mohammad Fathinasab3

  • 1National Iranian Oil Company, Ahvaz, Iran. hayanzaheri88@gmail.com.

Scientific reports
|November 4, 2024
PubMed
概括
此摘要是机器生成的。

一个新的集成算法增强了油井放置和现场开发的操作设置. 这种方法优于传统的遗传算法和粒子群优化,提高了生产效率.

关键词:
遗传算法 遗传算法 遗传算法粒子群集优化优化 粒子群集优化储水池模拟器 储水池模拟器井的位置模式 井的位置模式

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科学领域:

  • 石油工程是石油工程中的一个.
  • 计算科学 计算科学

背景情况:

  • 优化井位置和操作设置对于最大限度地提高油气田产量至关重要.
  • 复杂的地质,流体流动和经济因素使优化具有挑战性和计算密集度.
  • 现有的模拟方法往往耗时,并且缺乏对高维的解决方案空间的一般方法.

研究的目的:

  • 为了比较基因算法 (GA) 和粒子群优化 (PSO) 的效率和可靠性.
  • 引入和评估一种结合GA和PSO的新型集成算法,以改善井道模式优化.
  • 在现场开发中解决传统优化算法的局限性.

主要方法:

  • 基因算法 (GA) 和粒子群优化 (PSO) 性能的分析和比较.
  • 开发一种新的集成算法,利用PSO的内存来提高GA的效率.
  • 在各种井样模式优化场景中测试集成算法.

主要成果:

  • 新开发的集成算法与独立的GA和PSO相比,表现优越.
  • 综合算法为不合格的解决方案提供了更多的机会,通过结合PSO的速度概念来改进.
  • 单靠GA和PSO并不能保证最佳解决方案,而新方法显示了更好的结果.

结论:

  • 集成算法为现场开发中井模式优化提供了更有效和可靠的方法.
  • 这种新的方法通过结合GA和PSO的优势来提高搜索性能.
  • 这些发现突出了通过先进的计算技术对优化石油和天然气生产的重大贡献.