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

What is Evolutionary History?02:35

What is Evolutionary History?

43.0K
Scientists record evolutionary history by analyzing fossil, morphological, and genetic data. The fossil record documents the history of life on Earth and provides evidence for evolution. However, both fossil and living organisms offer evidence that outlines Earth’s evolutionary history.
43.0K
Mixtures of Acids03:27

Mixtures of Acids

21.6K
The pH of a solution containing an acid can be determined using its acid dissociation constant and its initial concentration. If a solution contains two different acids, then its pH can be determined using one of several methods depending upon the relative strength of the acids and their dissociation constants.
A Mixture of a Strong Acid and a Weak Acid
In a mixture of a strong acid and a weak acid, the strong acid dissociates completely and becomes a source of almost all the hydronium ions...
21.6K
Mixtures of Acids01:19

Mixtures of Acids

1.1K
The pH of a solution containing an acid can be determined using its acid dissociation constant and initial concentration. If a solution contains two different acids, then its pH can be determined using one of several methods depending on the relative strength of the acids and their dissociation constants.
In a strong and weak acid mixture, the strong acid dissociates completely and becomes a source of almost all the hydronium ions present in the solution. In contrast, the weak acid shows...
1.1K
Evolutionary Psychology01:20

Evolutionary Psychology

973
Evolutionary psychology explores the origins of human behavior and mental processes by framing them within the context of natural selection, a theory famously propounded by Charles Darwin. This field asserts that many behaviors common across human societies — ranging from instinctive fear reactions to complex social interactions — arose as evolutionary adaptations. These adaptations enhanced the survival and reproductive success of our ancestors, thereby becoming embedded in the...
973
Criticisms of the Evolutionary Perspective01:23

Criticisms of the Evolutionary Perspective

348
In a study where individuals posing as strangers offered compliments and proposed casual sex to students, the responses differed significantly based on gender. Not a single woman accepted the proposal, while 70% of the men agreed. This outcome provides a useful scenario to explore through the lens of evolutionary psychology and social learning theory, highlighting the diverse perspectives on human sexual behaviors.
Evolutionary psychology provides one explanation for these findings, suggesting...
348
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

6.9K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
6.9K

You might also read

Related Articles

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

Sort by
Same author

Enhancing X-ray Image Classification through Heterogeneous Federated Learning with Natural Image-Augmented Models.

IEEE transactions on pattern analysis and machine intelligence·2026
Same author

Developing and Testing a Brief Mindfulness Just-in-Time Adaptive Intervention to Reduce Stress Among Caregivers of People With Dementia: Quasi-Experimental Study.

JMIR aging·2026
Same author

Enhancing Generalization and Scalability for Multi-Objective Optimization with Population Pre-Training.

Evolutionary computation·2026
Same author

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis.

IEEE transactions on medical imaging·2026
Same author

Spatiotemporal Decoupled Learning for Spiking Neural Networks.

IEEE transactions on neural networks and learning systems·2026
Same author

Explainable Molecular Property Prediction: Aligning Chemical Concepts With Predictions via Language Models.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

An Evolutionary Algorithm Assisted by an Ensemble of Pareto-Optimal Surrogate Models.

IEEE transactions on cybernetics·2026
Same journal

A Quantum Self-Attention Neural Network Model on Quantum Circuits.

IEEE transactions on cybernetics·2026
Same journal

Semi-Explicit Solution of Some Discrete-Time Higher-Order-Cost Mean-Field-Type Control.

IEEE transactions on cybernetics·2026
Same journal

A Novel One-Step Small Object Detector for Autonomous Aerial Vehicles.

IEEE transactions on cybernetics·2026
Same journal

Online Data-Driven-Based Optimal Output Tracking Control Without Initial Stabilizing Policy.

IEEE transactions on cybernetics·2026
Same journal

Digital Redesign-Based Interval State Estimation for Continuous Systems With Aperiodic Discrete Measurements.

IEEE transactions on cybernetics·2026
See all related articles

Related Experiment Video

Updated: Jan 25, 2026

A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
13:54

A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM

Published on: August 18, 2023

5.9K

A Mixture-of-Experts Prediction Framework for Evolutionary Dynamic Multiobjective Optimization.

Rethnaraj Rambabu, Prahlad Vadakkepat, Kay Chen Tan

    IEEE Transactions on Cybernetics
    |April 26, 2019
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel mixture-of-experts framework to enhance prediction of Pareto-optimal solutions (POS) in dynamic multiobjective optimization, improving search efficiency in changing environments.

    More Related Videos

    Reaction Kinetics and Combustion Dynamics of I4O9 and Aluminum Mixtures
    09:16

    Reaction Kinetics and Combustion Dynamics of I4O9 and Aluminum Mixtures

    Published on: November 7, 2016

    11.4K
    Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
    10:29

    Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

    Published on: May 9, 2025

    2.2K

    Related Experiment Videos

    Last Updated: Jan 25, 2026

    A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
    13:54

    A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM

    Published on: August 18, 2023

    5.9K
    Reaction Kinetics and Combustion Dynamics of I4O9 and Aluminum Mixtures
    09:16

    Reaction Kinetics and Combustion Dynamics of I4O9 and Aluminum Mixtures

    Published on: November 7, 2016

    11.4K
    Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
    10:29

    Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

    Published on: May 9, 2025

    2.2K

    Area of Science:

    • Computational Intelligence
    • Optimization Theory
    • Machine Learning

    Background:

    • Dynamic multiobjective optimization (DMOO) necessitates tracking evolving Pareto-optimal solutions (POS) in dynamic environments.
    • Existing prediction mechanisms use past population data to accelerate convergence to true POS upon environmental change.
    • Robust POS prediction remains a challenge in DMOO.

    Purpose of the Study:

    • To propose a novel mixture-of-experts (MoE)-based ensemble framework for robust prediction of Pareto-optimal solutions (POS) in dynamic multiobjective optimization.
    • To enhance the accuracy and efficiency of POS tracking in changing environments.
    • To improve the overall performance of dynamic optimization algorithms.

    Main Methods:

    • An ensemble framework utilizing multiple prediction mechanisms is developed.
    • A gating network dynamically switches between predictors based on their performance over time.
    • The framework is evaluated on 13 benchmark dynamic multiobjective optimization problems.

    Main Results:

    • The proposed MoE framework significantly improves dynamic optimization performance.
    • Performance gains are particularly notable for problems with distinct dynamic POS shifts in decision space.
    • The framework demonstrates effectiveness in handling problems with highly nonlinear decision variable linkages.

    Conclusions:

    • The mixture-of-experts ensemble framework offers a robust approach to POS prediction in dynamic multiobjective optimization.
    • This method enhances the ability to track evolving optimal solutions in complex, changing environments.
    • The findings suggest a significant advancement in dynamic optimization strategies, especially for challenging problem types.