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
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

714
The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
714
Control of Power Flow01:30

Control of Power Flow

653
There are several methods to control power flow in power systems:
653
Distributed Loads01:19

Distributed Loads

927
Distributed loads are a common type of load that engineers and scientists encounter in various practical situations. Distributed loads often refer to a type of load spread over a surface or a structure and can be modeled as continuous force per unit area.
For example, consider a bookshelf filled with books stacked vertically adjacent to each other. The weight of the books is evenly distributed over the length of the shelf. As a result, the pressure at different locations on the surface of the...
927
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

576
The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
576
Multimachine Stability01:25

Multimachine Stability

532
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:
532

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

Retracted: Public Security Video Image Detection System Construction Platform in Cloud Computing Environment.

Computational intelligence and neuroscience·2023
Same author

Retracted: Design and Implementation of Human Motion Recognition Information Processing System Based on LSTM Recurrent Neural Network Algorithm.

Computational intelligence and neuroscience·2023
Same author

Retracted: Music Waveform Analysis Based on SOM Neural Network and Big Data.

Computational intelligence and neuroscience·2023
Same author

Retracted: Language Processing Model Construction and Simulation Based on Hybrid CNN and LSTM.

Computational intelligence and neuroscience·2023
Same author

Retracted: A Sensor-Based IoT Data Collection and Marine Economy Collaborative Innovation Method.

Computational intelligence and neuroscience·2023
Same author

Retracted: Performance Art Video Action Management Oriented to 6G Wireless Transmission Technology.

Computational intelligence and neuroscience·2023
Same journal

RETRACTION: Real-Time Modulation of Physical Training Intensity Based on Wavelet Recursive Fuzzy Neural Networks.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Multidimensional Heterogeneous Network Link Adaptation Based on Mobile Environment.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Framework to Segment and Evaluate Multiple Sclerosis Lesion in MRI Slices Using VGG-UNet.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Facial Emotion Recognition Using a Novel Fusion of Convolutional Neural Network and Local Binary Pattern in Crime Investigation.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Automatic Intelligent System Using Medical of Things for Multiple Sclerosis Detection.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Intangible Cultural Heritage Reproduction and Revitalization: Value Feedback, Practice, and Exploration Based on the IPA Model.

Computational intelligence and neuroscience·2026
查看所有相关文章

相关实验视频

Updated: Jan 9, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

1.1K

撤回:虚拟发电厂的分布式调度策略使用区块链背景下的粒子群优化神经网络.

Computational Intelligence And Neuroscience

    Computational intelligence and neuroscience
    |December 1, 2025
    PubMed
    概括
    此摘要是机器生成的。

    这篇文章已被撤回. 原始研究不再被认为是有效的科学文献.

    更多相关视频

    Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
    06:04

    Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

    Published on: February 14, 2025

    987

    相关实验视频

    Last Updated: Jan 9, 2026

    Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
    05:30

    Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

    Published on: September 8, 2023

    1.1K
    Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
    06:04

    Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

    Published on: February 14, 2025

    987

    科学领域:

    • 本节不适用,因为该条款已被收回.

    背景情况:

    • 本节不适用,因为该条款已被收回.

    研究的目的:

    • 本节不适用,因为该条款已被收回.

    主要方法:

    • 本节不适用,因为该条款已被收回.

    主要成果:

    • 本节不适用,因为该条款已被收回.

    结论:

    • 本节不适用,因为该条款已被收回.