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相关概念视频

Three-Dimensional Force System:Problem Solving01:30

Three-Dimensional Force System:Problem Solving

660
A three-dimensional force system refers to a scenario in which three forces act simultaneously in three different directions. This type of problem is commonly encountered in physics and engineering, where it is necessary to calculate the resultant force on the system, which can then be used to predict or analyze the behavior of the object or structure under consideration.
To solve a three-dimensional force system, first resolve each force into its respective scalar components. Do this using...
660
Normal and Tangetial Components: Problem Solving01:24

Normal and Tangetial Components: Problem Solving

177
Consider a man with a mass of 70 kg seated in a chair connected to a pin support through a member BC. If the man maintains an upright position, the task is to determine the horizontal and vertical reactions of the chair on the man when the member makes a 45° angle with the horizontal. At this moment, the man has a speed of 5 m/s, increasing at a rate of 1 m/s².
177
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

639
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...
639
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

48
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...
48
Decision Making: P-value Method01:09

Decision Making: P-value Method

5.3K
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
5.3K
Friction: Problem Solving01:21

Friction: Problem Solving

219
Friction is an essential force that influences the motion of objects in daily life. Depending on the situation, it can be either beneficial or problematic. Consider a bus with a mass of three megagrams and its center of mass at a specific point, moving along a banked road at a constant speed. The coefficient of static friction between the tires and the road is 0.5. Find the maximum angle of the banked road at which the bus would not slip or tip.
Initially, a visual representation of the...
219

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相关实验视频

Updated: Jun 21, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

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改进了模糊多目标运输问题,使用三角模糊数字.

A Kokila1, G Deepa1

  • 1Department of Mathematics, SAS, Vellore Institute of Technology, Vellore, Tamil Nadu, India.

Heliyon
|July 15, 2024
PubMed
概括

这项研究解决了模糊的多目标运输问题 (FMOTP),不确定成本,供应和需求. 一种新的方法将模糊的数据转化为清晰的值,为复杂的物流挑战提供最佳解决方案.

科学领域:

  • 运营研究 运营研究
  • 模糊的数学 模糊的数学
  • 供应链管理 供应链管理

背景情况:

  • 运输问题往往涉及不确定的参数,如成本,供应和需求,由于市场波动.
  • 传统方法与不准确的数据作斗争,需要模糊的方法.

研究的目的:

  • 在模糊的环境中开发一个强大的方法来解决多目标运输问题 (MOTP).
  • 使用模糊数字处理不准确的运输成本,供应和需求数据.
  • 在不确定的条件下确定模糊MOTP (FMOTP) 的最佳解决方案.

主要方法:

  • 用模糊参数对FMOTP进行数学表述.
  • 模糊算法的应用,将FMOTP分解为低级,中级和高级的脆脆的MOTP.
  • 将模糊的问题减少到一个清晰的MOTP.
  • 利用和平均值来解决每个目标函数.

主要成果:

  • 介绍了解决FMOTP的系统程序.
  • 该方法有效地将模糊参数转换为可解决的清晰格式.
  • 这种方法有助于为具有固有的不确定性的运输物流找到最佳解决方案.
关键词:
模糊的多目标运输问题模糊的最佳解决方案 模糊的最佳解决方案一个模糊的设置.的平均值是指的平均值.三角形的模糊数字.

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结论:

  • 拟议的方法为解决FMOTP提供了一个有效的框架.
  • 这项研究有助于在不确定性下在运输和物流领域做出更好的决策.
  • 该技术增强了在动态和不精确的市场环境中找到最佳解决方案的能力.