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

Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

1.1K
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...
1.1K
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

384
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...
384
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

282
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...
282
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

238
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
238
Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

1.1K
A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of the...
1.1K
Two-Dimensional Force System: Problem Solving01:29

Two-Dimensional Force System: Problem Solving

1.2K
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...
1.2K

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

Self-powered intelligence for personalized healthcare.

National science review·2026
Same author

Influence of High-Volume Calcined Phosphogypsum on Mechanical Properties and Freeze-Thaw Resistance of Supersulfated Slag Cement Concrete.

Materials (Basel, Switzerland)·2026
Same author

Maximum utilization of all elements in biomass waste.

Innovation (Cambridge (Mass.))·2026
Same author

Integrated 16S rRNA gene sequencing and LC-MS/MS-based metabolomics to explore potential mechanisms of Coptidis Rhizoma-Aucklandiae Radix herb pair against antibiotic-associated diarrhea.

Journal of chromatography. B, Analytical technologies in the biomedical and life sciences·2026
Same author

Augmented Reality Tourism Technology Based on an Improved ORB Algorithm and Homography Matrix.

Journal of visualized experiments : JoVE·2026
Same author

Modular Functionalized Gates for Field-Effect Transistor Biosensors Enabling Reliable Detection of Trace miRNAs.

ACS nano·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
Same journal

Digital Redesign-Based Interval State Estimation for Continuous Systems With Aperiodic Discrete Measurements.

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

相关实验视频

Updated: Jan 14, 2026

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

Published on: December 9, 2012

13.4K

数据驱动学习 分布优化异质线性多代理系统的数据驱动学习.

Haizhou Yang, Kedi Xie, Maobin Lu

    IEEE transactions on cybernetics
    |January 12, 2026
    PubMed
    概括
    此摘要是机器生成的。

    本研究介绍了一种数据驱动的自适应动态编程 (ADP) 方法,用于多代理系统的分布式优化,消除了对先前系统知识的需求. 该方法确保代理商达成最佳共识,在液压轮控制中证明了这一点.

    相关实验视频

    Last Updated: Jan 14, 2026

    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

    Published on: December 9, 2012

    13.4K

    科学领域:

    • 控制系统工程 控制系统工程
    • 优化理论 优化理论
    • 人工智能的人工智能

    背景情况:

    • 分布式优化对于多代理系统至关重要.
    • 不同质的系统和定向网络带来了独特的挑战.
    • 现有的方法往往需要对系统动态有完整的了解.

    研究的目的:

    • 为异质线性多代理系统开发数据驱动的分布式优化控制定律.
    • 为了克服未知的系统动态的限制.
    • 为了在代理人之间达成最佳的输出共识.

    主要方法:

    • 基于自适应动态编程 (ADP) 的数据驱动方法.
    • 从状态和输入数据中确定反收益.
    • 使用反获取和运行数据重建系统动态.
    • 通过稳定状态方程设计控制定律参数.

    主要成果:

    • 在没有先前的系统动态知识的情况下,开发了一个新的分布式优化控制定律.
    • 确定性等价原则保证了向最佳解决方案的趋同.
    • 在全球成本函数的最佳状态下,对所有代理实现了输出共识.

    结论:

    • 拟议的数据驱动的ADP方法有效地解决了异质多代理系统的分布式优化问题.
    • 该方法通过对液压轮机功率共享控制的应用来验证.
    • 这种方法为具有未知的动态的复杂网络系统提供了强大的解决方案.