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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

38
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...
38
Genetic Drift03:33

Genetic Drift

39.2K
Natural selection—probably the most well-known evolutionary mechanism—increases the prevalence of traits that enhance survival and reproduction. However, evolution does not merely propagate favorable traits, nor does it always benefit populations.
39.2K
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

93
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...
93
Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

57.8K
In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).
57.8K
Inclusive Fitness00:57

Inclusive Fitness

35.9K
Most altruistic behavior—in which one animal helps another at a cost to themselves—occurs between relatives. Scientists think these altruistic behaviors evolved because they increase the inclusive fitness of the animal providing help.
35.9K
Woodward–Hoffmann Selection Rules and Microscopic Reversibility01:34

Woodward–Hoffmann Selection Rules and Microscopic Reversibility

3.0K
Electrocyclic reactions, cycloadditions, and sigmatropic rearrangements are concerted pericyclic reactions that proceed via a cyclic transition state. These reactions are stereospecific and regioselective. The stereochemistry of the products depends on the symmetry characteristics of the interacting orbitals and the reaction conditions. Accordingly, pericyclic reactions are classified as either symmetry-allowed or symmetry-forbidden. Woodward and Hoffmann presented the selection criteria for...
3.0K

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

U-SplitDoRA: an improved privacy-preserved U-shaped split parameter-efficient fine-tuning framework through weight decomposition for large language models.

Frontiers in artificial intelligence·2026
Same author

A quantum resilient deepfake detection framework using enhanced resnext and post quantum cryptography defence.

Scientific reports·2026
Same author

Graph-enhanced multimodal fusion of vascular biomarkers and deep features for diabetic retinopathy detection.

Frontiers in artificial intelligence·2026
Same author

Population diversity control based differential evolution algorithm using fuzzy system for noisy multi-objective optimization problems.

Scientific reports·2024
Same author

Deep Siamese domain adaptation convolutional neural network-based quaternion fractional order Meixner moments fostered big data analytical method for enhancing cloud data security.

Network (Bristol, England)·2024

相关实验视频

Updated: May 27, 2025

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

11.5K

一个基于模糊系统的自我适应的模拟算法,使用人口多样性控制来进行进化多目标优化.

Brindha Subburaj1, S Miruna Joe Amali2

  • 1School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, Tamilnadu, India. brindha.s@vit.ac.in.

Scientific reports
|February 17, 2025
PubMed
概括

本研究介绍了使用多样性控制 (F-MAD) 的基于Fuzzy的Memetic算法,这是一个强大的,自我适应的进化算法,用于多目标优化. 在基准问题上,F-MAD表现出卓越的性能,在没有广泛的参数调整的情况下,其性能优于最先进的方法.

关键词:
进化计算是一种进化计算.这是一个模糊系统.记忆力算法 记忆力算法多目标优化多目标优化人口多样性的多样性

更多相关视频

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

7.4K
Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
20:36

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Published on: July 4, 2007

8.7K

相关实验视频

Last Updated: May 27, 2025

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

11.5K
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

7.4K
Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
20:36

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Published on: July 4, 2007

8.7K

科学领域:

  • 计算智能是一种计算智能.
  • 优化算法 优化算法
  • 进化计算是一种进化计算.

背景情况:

  • 进化算法需要对各种问题领域进行广泛的参数调整.
  • 现有的方法往往在过早的融合和平衡勘探-开发方面扎.
  • 多目标优化问题在寻找最佳解决方案方面存在重大挑战.

研究的目的:

  • 为多目标优化问题开发一个强大的,自我适应的模拟算法.
  • 通过结合全球和本地搜索策略来增强进化算法.
  • 创建一个自动调整参数的算法,减少手工微调的需要.

主要方法:

  • 使用多样性控制 (F-MAD) 开发了基于 Fuzzy 的记忆算法.
  • 集成差异演化 (DE) 具有受控的本地搜索程序.
  • 采用模糊系统来自我调整DE控制参数 (交叉率,缩放因子) 以管理人口多样性.

主要成果:

  • 在CEC 2009和DTLZ基准测试问题上,F-MAD表现优异.
  • 在 8/10 CEC 2009 问题和所有 7 个 DTLZ 问题上取得比最先进的算法更好的结果.
  • 统计分析 (弗里德曼等级测试) 证实了F-MAD的显著表现.

结论:

  • F-MAD为多目标优化提供了一种强大而自我适应的方法.
  • 该算法有效平衡勘探和开发,确保多样性和融合.
  • F-MAD的适应性使其适用于各种应用领域,而无需参数试错.