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

Framing Effects03:26

Framing Effects

Information is everywhere and its presentation—such as how and when items are presented—can impact our perceptions and decisions surrounding the info. This broad concept umbrellas framing effects—influences that occur due to the way information is framed in its appearance, whether it’s purely the order or the specific wording of a message. Let’s take a look at numerous ways in which two versions of something can objectively say the same thing, yet we respond in different ways based on the...
Cluster Sampling Method01:20

Cluster Sampling Method

Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
Randomized Experiments01:13

Randomized Experiments

The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
Frames: Problem Solving I01:24

Frames: Problem Solving I

Consider a jib crane with an external load suspended from the pulley. The dimensions of the crane members are shown in the figure. A systematic analysis of the frame structure is required to determine the reaction forces at the pin joints, assuming that the pulleys are frictionless.
Frames: Problem Solving II01:26

Frames: Problem Solving II

Consider a hydraulic hoist supporting a load of 1 kN. Assuming a simplified schematic representation of this frame structure, the force acting on BD and BF members can be determined.
Statically Indeterminate Problem Solving01:16

Statically Indeterminate Problem Solving

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...

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

Effect of polypropylene microplastics on the performance of membrane bioreactors in wastewater treatment.

Environmental research·2025
Same author

Correspondence between Euler charges and nodal-line topology in Euler semimetals.

Science advances·2025
Same author

Development of nanofiber facial mask inspired by the multi-function of dried ginger (Zingiberis Rhizoma) essential oil.

Scientific reports·2025
Same author

Identification of common diagnostic genes and molecular pathways in endometriosis and systemic lupus erythematosus by machine learning approach and in vitro experiment.

International journal of medical sciences·2025
Same author

Application of Ordered Porous Silica Materials in Drug Delivery: A Review.

Molecules (Basel, Switzerland)·2024
Same author

Complete genome sequence of a novel iflavirus from wheat sawfly (Dolerus tritici).

Archives of virology·2024
Same journal

Research on a Regional Availability Evaluation Model for Road-Area High-Entropy Energy Based on Synergy Factors.

Entropy (Basel, Switzerland)·2026
Same journal

Atmospheric Turbulence Channel Modeling and Performance Analysis of a CO-ZP-OFDM Coherent Optical Communication System for UAV Air-to-Ground Scenarios.

Entropy (Basel, Switzerland)·2026
Same journal

Information Geometry and Asymptotic Theory for SMML Estimators.

Entropy (Basel, Switzerland)·2026
Same journal

Correlation Entropy and Power-Law Kinetics.

Entropy (Basel, Switzerland)·2026
Same journal

Research on the Contagion of Systemic Financial Risk Under the Impact of Climate Risks-From the Perspective of Complex Networks and Machine Learning.

Entropy (Basel, Switzerland)·2026
Same journal

The Statistical-Mechanical Meaning of the Wave Function of Quantum Mechanics.

Entropy (Basel, Switzerland)·2026
查看所有相关文章

相关实验视频

Updated: May 10, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.5K

CNN-HT:一个两阶段的算法选择框架.

Siyi Xu1, Wenwen Liu1, Chengpei Wu1

  • 1School of Computer Science, Sichuan Normal University, Chengdu 610068, China.

Entropy (Basel, Switzerland)
|March 28, 2024
PubMed
概括
此摘要是机器生成的。

CNN-HT框架有效地为未知的问题选择最佳算法. 这种两阶段的方法使用卷积神经网络 (CNN) 和假设测试 (HT) 来实现卓越的性能和适应性.

关键词:
选择算法选择算法这是分类分类的分类.卷积神经网络是一种卷积神经网络.探索性景观分析 探索性景观分析功能选择 功能选择假设测试 测试 假设测试

更多相关视频

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.5K
Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.7K

相关实验视频

Last Updated: May 10, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.5K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.5K
Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.7K

科学领域:

  • 计算机科学 计算机科学
  • 人工智能的人工智能
  • 优化优化 优化优化

背景情况:

  • 没有免费午餐定理强调了对特定问题的算法选择的需要.
  • 现有的单阶段算法选择方法通常需要为新算法组合进行完整的重新培训.

研究的目的:

  • 介绍CNN-HT,一个新的两阶段算法选择框架.
  • 通过利用卷积神经网络 (CNN) 来进行问题分类和假设测试 (HT) 来进行算法推来改进算法选择.

主要方法:

  • 利用探索性景观分析 (ELA) 功能作为问题分类的输入.
  • 采用卷积神经网络 (CNN) 进行初始问题分类,然后进行假设测试 (HT) 进行算法选择.
  • 实施特征选择技术以优化分类模型.

主要成果:

  • 在使用CNN的问题分类中获得了96%的平均准确性,超过了随机森林和支持向量机.
  • 在特征选择后,分类准确度提高到98.8%,提高性能并降低计算成本.
  • 与单个算法和其他组合方法相比,CNN-HT框架的表现优越,平均排名更好.

结论:

  • CNN-HT框架为优化中的算法选择提供了有效和可适应的解决方案.
  • 两阶段方法允许在不需要完全重新训练模型的情况下进行修改,比单阶段方法有显著的改进.
  • 在问题分类中取得的高精度验证了CNN-HT方法第一阶段的有效性.