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Related Concept Videos

Distributed Loads01:19

Distributed Loads

1.1K
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...
1.1K
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

1.3K
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...
1.3K
Elastic Curve from the Load Distribution01:16

Elastic Curve from the Load Distribution

588
The structural behavior of beams under distributed loads is critical for engineering analysis, which focuses on predicting how beams bend and react under such conditions. Different types of beams (e.g., cantilever, supported, or overhanging) behave differently under distributed load conditions.
For all beams, the analysis of the beam's reaction to distributed loads begins by understanding the relationship between a beam's load and the resulting shear forces and bending moments. Initially, this...
588
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

777
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.
777
Relation Between the Distributed Load and Shear01:23

Relation Between the Distributed Load and Shear

1.2K
Understanding the relationship between the distributed load and shear force in structural analysis is crucial for analyzing beams subjected to various loading conditions. Consider the case of a beam experiencing a distributed load, two concentrated loads, and a couple moment.
1.2K
Load-frequency control01:28

Load-frequency control

894
Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
894

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Related Experiment Videos

Efficient resources provisioning based on load forecasting in cloud.

Rongdong Hu1, Jingfei Jiang1, Guangming Liu2

  • 1School of Computer, National University of Defense Technology, Changsha 410073, China.

Thescientificworldjournal
|April 5, 2014
PubMed
Summary
This summary is machine-generated.

This study introduces KSwSVR, a novel load forecasting method for cloud computing. It improves resource allocation efficiency and reduces consumption while meeting quality of service demands.

Related Experiment Videos

Area of Science:

  • Cloud Computing
  • Machine Learning
  • Resource Management

Background:

  • Cloud providers face challenges in balancing Quality of Service (QoS) with resource utilization.
  • Accurate prediction of future resource demand is crucial for efficient, fine-grained resource allocation.

Purpose of the Study:

  • To propose a multi-step-ahead load forecasting method for dynamic cloud environments.
  • To develop an efficient resource provisioning strategy based on predicted load.

Main Methods:

  • Integration of an improved Support Vector Regression (SVR) algorithm with a Kalman smoother, termed KSwSVR.
  • Validation using public trace data from multiple resource types, comparing KSwSVR against AR, BPNN, and standard SVR.
  • Development of a resource provisioning strategy leveraging the forecasting results.

Main Results:

  • KSwSVR demonstrated high prediction accuracy, stability, and adaptability in cloud environments.
  • The proposed resource provisioning strategy effectively reduced resource consumption.
  • Service Level Agreements (SLAs) requirements were met concurrently with reduced consumption.

Conclusions:

  • The KSwSVR method provides a robust solution for multi-step-ahead load forecasting in cloud computing.
  • The integrated approach enables efficient resource provisioning, optimizing utilization and QoS.
  • This strategy offers a practical solution for enhancing cloud resource management.