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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

101
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...
101
Statically Indeterminate Problem Solving01:16

Statically Indeterminate Problem Solving

498
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...
498
Sampling Plans01:23

Sampling Plans

274
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...
274
Response Surface Methodology01:16

Response Surface Methodology

267
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:
267
Multimachine Stability01:25

Multimachine Stability

230
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
230
Simplified Synchronous Machine Model01:30

Simplified Synchronous Machine Model

332
The Synchronous Machine Model is a fundamental tool in analyzing and ensuring the transient stability of power systems. This model simplifies the representation of a synchronous machine under balanced three-phase positive-sequence conditions, assuming constant excitation and ignoring losses and saturation. The model is pivotal for understanding the behavior of synchronous generators connected to a power grid, particularly during transient events.
In this model, each generator is connected to a...
332

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相关实验视频

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Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
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基于模拟的框架用于随机的多模式资源受限制的项目调度.

Ali Rahimifard1, Isa Nakhai-Kamalabadi2, Kaveh Khalili-Damghani1

  • 1Department of Industrial Engineering, ST.C., Islamic Azad University, Tehran, Iran.

MethodsX
|July 24, 2025
PubMed
概括
此摘要是机器生成的。

本研究提出了一个新的模拟框架,用于不确定的项目调度. 它结合了离散事件模拟 (DES) 和多代理系统 (MAS) 来改善复杂,资源有限的环境中的规划.

关键词:
离散事件模拟 (DES)多个代理系统 (MAS)多模式资源受限项目调度模拟建模,任何逻辑模型.随机项目调度 随机项目调度塔古奇设计的实验设计.

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科学领域:

  • 运营研究 运营研究
  • 项目管理 项目管理
  • 模拟建模模的模拟模型.

背景情况:

  • 由于活动持续时间不确定和资源有限,项目计划是复杂的.
  • 现有的模型往往难以捕捉现实世界的动态不确定性和相互作用.
  • 随机的多模式资源受限项目调度问题 (SN-MMRCPSP) 提出了重大规划挑战.

研究的目的:

  • 引入一种新的基于模拟的框架来解决SN-MMRCPSP.
  • 在不确定的和动态的环境中提高项目规划效率.
  • 改善对资源有限的复杂项目的决策.

主要方法:

  • 开发了一种混合离散事件模拟 (DES) 和多代理系统 (MAS) 架构.
  • 塔古奇实验设计 (DOE) 用于优化执行模式.
  • 该框架整合了模拟用于不确定性建模和MAS用于复杂相互作用.

主要成果:

  • 拟议的混合DES-MAS模型有效地捕捉了项目的不确定性和相互作用.
  • 塔古奇能源部确定了最佳执行模式,提高了模型的稳定性.
  • 案例研究和基准比较验证了该框架的实用性和有效性.

结论:

  • 开发的模拟框架为SN-MMRCPSP提供了一个强大的解决方案.
  • 这种方法显著改善了不确定性下的项目规划和决策.
  • DES和MAS的整合为管理复杂项目提供了一个强大的工具.