Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

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

47
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...
47
Three-Dimensional Force System:Problem Solving01:30

Three-Dimensional Force System:Problem Solving

657
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...
657
Two-Dimensional Force System: Problem Solving01:29

Two-Dimensional Force System: Problem Solving

556
Solving problems related to two-dimensional force systems is an essential aspect of mechanics and engineering. By applying the principles of vector analysis and force equilibrium, one can determine the effect of multiple forces acting on an object in a two-dimensional space.
The first step to solving a two-dimensional force system problem is to draw a free-body diagram of the object under consideration. This diagram helps identify all the external forces acting on the object, including their...
556
Collisions in Multiple Dimensions: Problem Solving01:06

Collisions in Multiple Dimensions: Problem Solving

3.7K
In multiple dimensions, the conservation of momentum applies in each direction independently. Hence, to solve collisions in multiple dimensions, we should write down the momentum conservation in each direction separately. To help understand collisions in multiple dimensions, consider an example.
A small car of mass 1,200 kg traveling east at 60 km/h collides at an intersection with a truck of mass 3,000 kg traveling due north at 40 km/h. The two vehicles are locked together. What is the...
3.7K
Equation of Motion: General Plane motion - Problem Solving01:16

Equation of Motion: General Plane motion - Problem Solving

174
Consider a lawn roller with a mass of 100 kg, a radius of 0.2 meters, and a radius of gyration of 0.15 meters. A force of 200 N is applied to this roller, angled at 60 degrees from the horizontal plane. What will be the angular acceleration of the lawn roller?
The friction between the roller and the ground is characterized by two coefficients. The static friction coefficient is 0.15, while the kinetic friction coefficient is 0.1. These values are crucial in understanding the interaction between...
174
Statically Indeterminate Problem Solving01:16

Statically Indeterminate Problem Solving

369
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...
369

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

High and low body mass index increases the risk of short-term postoperative complications following total shoulder arthroplasty.

JSES international·2025
Same author

Beam steering by two vertically faced metasurfaces using polarization free unit cells with three operating modes.

Scientific reports·2025
Same author

Identifying risk factors for 30-day readmission after outpatient total shoulder arthroplasty to aid in patient selection.

JSES international·2023
Same author

Solving time delay fractional optimal control problems via a Gudermannian neural network and convergence results.

Network (Bristol, England)·2023
Same author

Abnormal preoperative platelet count may predict postoperative complications following shoulder arthroplasty.

JSES international·2022
Same author

Chronic steroid use and readmission following total shoulder arthroplasty.

JSES international·2022

相关实验视频

Updated: Jun 17, 2025

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models
14:14

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models

Published on: August 12, 2018

8.8K

通过投影神经动力学模型解决一般的凸二次数多目标优化问题.

Mohammadreza Jahangiri1, Alireza Nazemi1

  • 1Faculty of Mathematical Sciences, Shahrood University of Technology, P.O. Box 3619995161- 316, Shahrood, Iran.

Cognitive neurodynamics
|August 6, 2024
PubMed
概括

本研究介绍了一种稳定的神经网络模型,以找到凸二次多目标编程问题 (CQMPP) 的最佳解决方案. 该方法通过使用加权和投影网络有效地确定帕雷托最佳解决方案.

科学领域:

  • 优化优化 优化优化
  • 人工智能的人工智能
  • 应用数学 应用数学 应用数学

背景情况:

  • 凸的二次式多目标编程问题 (CQMPP) 是复杂的优化挑战.
  • 找到帕雷托最佳解决方案 (POS) 需要高效的计算方法.

研究的目的:

  • 开发一个稳定和全球融合的神经网络模型来解决CQMPP.
  • 通过多样化权重值,有效地确定帕雷托最佳解决方案.

主要方法:

  • 使用加权总和方法,CQMPP被转化为一个单一目标问题.
  • 多个投影神经网络被用来寻找帕雷托最佳解决方案.
  • 利亚普诺夫理论被用来建立神经网络方法的稳定性和全球融合.

主要成果:

  • 拟议的神经网络模型在Lyapunov的意义上表现出稳定性.
  • 该模型被证明是全球趋同到单一目标问题的确切最佳解决方案.
  • 模拟结果证实了提出的神经网络方法的可行性和效率.

结论:

  • 开发的神经网络模型为解决CQMPP提供了强大而有效的方法.
关键词:
收 收 收 收 收 收凸凸的二次式编程问题多目标优化问题多目标优化问题神经网络的神经网络的神经网络帕雷托最佳解决方案最佳解决方案稳定的稳定性 稳定的稳定性

更多相关视频

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
10:50

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

1.7K
Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.0K

相关实验视频

Last Updated: Jun 17, 2025

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models
14:14

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models

Published on: August 12, 2018

8.8K
Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
10:50

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

1.7K
Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.0K
  • 该方法为复杂的优化任务提供了一种可靠的方式来获得帕雷托最佳解决方案.
  • 基于利亚普诺夫稳定的理论基础确保了优化结果的可靠性.