Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

370
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...
370
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

800
Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...
800
Genetic Drift03:33

Genetic Drift

44.4K
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.
44.4K
Two-Dimensional Force System: Problem Solving01:29

Two-Dimensional Force System: Problem Solving

1.4K
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...
1.4K
Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

64.8K
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).
64.8K
Direction of Acceleration Vectors01:10

Direction of Acceleration Vectors

22.9K
Acceleration occurs when velocity changes in magnitude (an increase or decrease in speed), direction, or both. Although acceleration is in the direction of the change in velocity, it is not always in the direction of motion. When an object slows down, its acceleration is opposite to the direction of its motion. This is commonly referred to as deceleration. However, the term deceleration can cause confusion in analysis because it is not a vector; it does not point to a specific direction with...
22.9K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Unveiling the Power of Multi-Modal Template Update in RGBT Tracking.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same author

A principal brain-region analysis framework based on evolutionary decomposition for fNIRS brain-computer interfaces.

Journal of neural engineering·2026
Same author

Improving Generalization in Collision Avoidance for Multiple Unmanned Aerial Vehicles via Causal Representation Learning.

Sensors (Basel, Switzerland)·2025
Same author

Paying more attention on backgrounds: Background-centric attention for UAV detection.

Neural networks : the official journal of the International Neural Network Society·2025
Same author

Searching Discriminative Regions for Convolutional Neural Networks in Fundus Image Classification With Genetic Algorithms.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2024
Same author

Recent Advances in Trajectory Planning and Object Recognition for Robot Sensing and Control.

Sensors (Basel, Switzerland)·2024
Same journal

A New Human-Likeness and Comfort Index for Robot Movements Along Prescribed Paths.

IEEE transactions on cybernetics·2026
Same journal

Robust Semiglobal and Global Stabilization for Nonlinear Normal Form Systems by Time-Varying Feedback.

IEEE transactions on cybernetics·2026
Same journal

Adaptive Global Asymptotic Output Stabilization of Uncertain Nonlinear Systems Under Dynamic State/Input Quantization.

IEEE transactions on cybernetics·2026
Same journal

Accelerated Distributed Gradient Tracking for Constrained Aggregative Optimization Over Time-Varying Digraphs.

IEEE transactions on cybernetics·2026
Same journal

Small-Gain-Based Plug-and-Play Distributed Control Framework for DC Microgrids With Decentralized Reconfiguration.

IEEE transactions on cybernetics·2026
Same journal

Prescribed-Time Impulsive Control of High-Order Integrator Systems.

IEEE transactions on cybernetics·2026
See all related articles

Related Experiment Video

Updated: Feb 23, 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

13.5K

A Decomposition-Based Many-Objective Evolutionary Algorithm With Two Types of Adjustments for Direction Vectors.

Xinye Cai, Zhiwei Mei, Zhun Fan

    IEEE Transactions on Cybernetics
    |September 1, 2017
    PubMed
    Summary
    This summary is machine-generated.

    A new algorithm, MaOEA/D-2ADV, improves evolutionary algorithms for many-objective optimization problems (MaOPs). It enhances convergence and diversity, especially for complex, irregular Pareto fronts.

    More Related Videos

    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

    12.3K
    Creating Objects and Object Categories for Studying Perception and Perceptual Learning
    14:38

    Creating Objects and Object Categories for Studying Perception and Perceptual Learning

    Published on: November 2, 2012

    12.3K

    Related Experiment Videos

    Last Updated: Feb 23, 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

    13.5K
    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

    12.3K
    Creating Objects and Object Categories for Studying Perception and Perceptual Learning
    14:38

    Creating Objects and Object Categories for Studying Perception and Perceptual Learning

    Published on: November 2, 2012

    12.3K

    Area of Science:

    • Computational intelligence
    • Optimization algorithms

    Background:

    • Decomposition-based multiobjective evolutionary algorithms are effective for many-objective optimization problems (MaOPs).
    • Existing algorithms face challenges with convergence and diversity on irregular Pareto fronts (PFs), such as degenerate or disconnected ones.

    Purpose of the Study:

    • To propose a novel decomposition-based many-objective evolutionary algorithm with two types of direction vector adjustments (MaOEA/D-2ADV).
    • To enhance convergence speed and population diversity for MaOPs, particularly those with irregular PFs.

    Main Methods:

    • Initial search focused on boundary direction vectors for rapid convergence.
    • Gradual increase in direction vectors to approximate a complete PF.
    • A Pareto-dominance-based mechanism identifies and adjusts ineffective direction vectors to match irregular PF shapes.

    Main Results:

    • MaOEA/D-2ADV demonstrated efficiency on various many-objective optimization benchmark problems.
    • Extensive experiments validated the algorithm's performance.
    • Component-wise analysis confirmed the effectiveness of each part of MaOEA/D-2ADV.

    Conclusions:

    • MaOEA/D-2ADV offers improved performance for MaOPs, especially those with challenging PFs.
    • The proposed direction vector adjustment strategies are effective in enhancing convergence and diversity.