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

Principle of Linear Impulse and Momentum for a Single Particle: Problem Solving01:23

Principle of Linear Impulse and Momentum for a Single Particle: Problem Solving

201
Consider a wooden box and a cylinder of known masses m1 and m2, respectively,  hanging from a ceiling with the help of a massless pulley system.
201
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

54
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...
54
Turbulent Flow: Problem Solving01:09

Turbulent Flow: Problem Solving

129
Carbonation is a process used to dissolve carbon dioxide gas in a liquid, commonly used in the production of carbonated beverages. Achieving efficient carbonation requires careful control of temperature, pressure, and flow conditions. By adjusting these parameters, carbonation efficiency can be maximized, producing a higher concentration of CO2 in the liquid.
Temperature is a key factor in CO2 solubility. In this case, the CO2 gas and the liquid are cooled to 20°C. Lower temperatures...
129
Three-Dimensional Force System:Problem Solving01:30

Three-Dimensional Force System:Problem Solving

667
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...
667
Two-Dimensional Force System: Problem Solving01:29

Two-Dimensional Force System: Problem Solving

571
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...
571
Collisions in Multiple Dimensions: Problem Solving01:06

Collisions in Multiple Dimensions: Problem Solving

4.2K
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...
4.2K

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

Deep learning-guided ligand generation for the strigolactone receptor ShHTL7.

Computational biology and chemistry·2026
Same author

Drug-coated balloons vs. drug-eluting stents for coronary artery disease: an updated systematic review and meta-analysis of randomized controlled trials with lesion-specific insights.

Frontiers in cardiovascular medicine·2026
Same author

Evolution-guided prioritization identifies a tissue-specific phosphorylation switch on herpes simplex virus 1 UL7 regulating viral replication and pathogenicity.

Journal of virology·2026
Same author

Mixture Pulsation Model-Based Decision-Making for Resource-Efficient Scheduling in Large-Scale Assembly Lines.

IEEE transactions on cybernetics·2026
Same author

Cinnamic acid-butenedioic lactone derivatives as crop protection agents: synthesis, bioactivity, and molecular docking studies.

Pest management science·2026
Same author

Effects of TiO<sub>2</sub> Nanoparticle Doping on the Micro-Arc Oxidation Coating Structure and Corrosion Resistance of 6061 Aluminum Alloy.

Molecules (Basel, Switzerland)·2026
Same journal

Relaxed Stability Conditions for Model Predictive Control of Hybrid Dynamical Systems Using Hybrid Recurrent Neural Networks.

IEEE transactions on cybernetics·2026
Same journal

An Evolutionary Algorithm Assisted by an Ensemble of Pareto-Optimal Surrogate Models.

IEEE transactions on cybernetics·2026
Same journal

A Quantum Self-Attention Neural Network Model on Quantum Circuits.

IEEE transactions on cybernetics·2026
Same journal

Semi-Explicit Solution of Some Discrete-Time Higher-Order-Cost Mean-Field-Type Control.

IEEE transactions on cybernetics·2026
Same journal

A Novel One-Step Small Object Detector for Autonomous Aerial Vehicles.

IEEE transactions on cybernetics·2026
Same journal

Online Data-Driven-Based Optimal Output Tracking Control Without Initial Stabilizing Policy.

IEEE transactions on cybernetics·2026
查看所有相关文章

相关实验视频

Updated: Jul 2, 2025

A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
13:54

A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM

Published on: August 18, 2023

4.6K

学习指导粒子搜索以实现动态多目标优化

Wei Song, Shaocong Liu, Xinjie Wang

    IEEE transactions on cybernetics
    |February 23, 2024
    PubMed
    概括
    此摘要是机器生成的。

    本研究介绍了粒子搜索指导网络 (PSGN),以有效解决动态多目标优化问题 (DMOPs). PSGN学会适应不断变化的环境,提供低计算成本的高效解决方案.

    更多相关视频

    The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
    11:53

    The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

    Published on: October 14, 2017

    11.6K
    A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents
    06:25

    A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents

    Published on: May 16, 2025

    148

    相关实验视频

    Last Updated: Jul 2, 2025

    A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
    13:54

    A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM

    Published on: August 18, 2023

    4.6K
    The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
    11:53

    The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

    Published on: October 14, 2017

    11.6K
    A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents
    06:25

    A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents

    Published on: May 16, 2025

    148

    科学领域:

    • 计算智能是一种计算智能.
    • 优化算法 优化算法
    • 机器学习 机器学习

    背景情况:

    • 动态多目标优化问题 (DMOPs) 涉及随时间变化的目标,对现有的算法构成重大挑战.
    • 当前的动态多目标算法 (DMOA) 难以学习和适应各种环境动态,从而限制了它们的有效性.
    • 在线有效地解决DMOP需要DMOA具有较低的计算开销.

    研究的目的:

    • 提出一个新的粒子搜索指导网络 (PSGN),以有效地解决各种动态的DMOP.
    • 通过强化学习使DMOA能够学习适应性搜索策略,以提高在动态环境中的性能.
    • 在不影响性能的情况下,为DMOP实现计算高效的解决方案.

    主要方法:

    • 开发一个粒子搜索指导网络 (PSGN) 来控制个别搜索行动,包括目标选择和加速系数.
    • 利用强化学习来训练PSGN,使其能够学习不同环境动态的最佳行动.
    • 实现增量学习,以高效调整 PSGN 隐藏节点和输出权重,以最大限度地降低计算成本.

    主要成果:

    • 拟议的PSGN展示了在各种动态中处理DMOP的能力.
    • PSGN实现了粒子搜索的计算效率指导,适合在线优化任务.
    • 对比实验表明,PSGN在解决DMOPs方面表现优于七个最先进的算法.

    结论:

    • 通过学习自适应性搜索策略,PSGN有效地解决了动态多目标优化的挑战.
    • 拟议的方法提供了一种计算效率高的方法来解决各种环境变化带来的DMOP.
    • PSGN代表了DMOA的重大进步,为复杂的动态优化任务提供了强大而高效的解决方案.