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

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...
In-vitro Mutagenesis01:16

In-vitro Mutagenesis

To learn more about the function of a gene, researchers can observe what happens when the gene is inactivated or “knocked out,” by creating genetically engineered knockout animals. Knockout mice have been particularly useful as models for human diseases such as cancer, Parkinson’s disease, and diabetes.
Conservative Site-specific Recombination and Phase Variation02:53

Conservative Site-specific Recombination and Phase Variation

Because the DNA segments are cut and reorganized in a direction-specific manner, site-specific recombination has emerged as an efficient genetic engineering technique. Flippase and Cyclization recombinases or Flp and Cre, respectively, are two members of the tyrosine recombinase family derived from bacteriophages, that are used to mediate site-specific DNA insertions, deletions, and targeted expression of proteins in mammalian cell lines.
The recognition sites for Cre recombinase called LoxP...
Woodward–Hoffmann Selection Rules and Microscopic Reversibility01:34

Woodward–Hoffmann Selection Rules and Microscopic Reversibility

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...
Evolution of New Traits in Microbes01:24

Evolution of New Traits in Microbes

Microorganisms evolve rapidly due to their large population sizes and short generation times, often exhibiting measurable changes within days under laboratory conditions. Natural selection acts on standing genetic variation, enabling the retention and amplification of beneficial traits that confer fitness advantages in changing environments.Adaptive Pigment Regulation in RhodobacterIn Rhodobacter, a genus of purple non-sulfur bacteria, light-harvesting pigments such as bacteriochlorophyll and...
Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

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).Mechanisms of Genetic VariationThe original sources of genetic variation are mutations,...

You might also read

Related Articles

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

Sort by
Same author

Along with its favorable prognostic role, CLCA2 inhibits growth and metastasis of nasopharyngeal carcinoma cells via inhibition of FAK/ERK signaling.

Journal of experimental & clinical cancer research : CR·2018
Same author

Hemopexin is required for adult neurogenesis in the subventricular zone/olfactory bulb pathway.

Cell death & disease·2018
Same author

Novel Mutations in SCN4A Gene Cause Myotonia Congenita with Scoliosis.

Chinese medical journal·2018
Same author

Plasma Hemopexin ameliorates murine spinal cord injury by switching microglia from the M1 state to the M2 state.

Cell death & disease·2018
Same author

Myt1L Promotes Differentiation of Oligodendrocyte Precursor Cells and is Necessary for Remyelination After Lysolecithin-Induced Demyelination.

Neuroscience bulletin·2018
Same author

[Inhibition of autophagy initiation stage enhances camptothecin-induced apoptosis in NCI-H1975 cells].

Xi bao yu fen zi mian yi xue za zhi = Chinese journal of cellular and molecular immunology·2018
Same journal

Multiphysics Investigation on Thermal Characteristics of Internal Bio-Inspired V-Ribbed Cooling Channels for Outer Rotor PMSM.

Biomimetics (Basel, Switzerland)·2026
Same journal

Smart Logistics Model for Supply Chain Management via Brain-Inspired Geometric Deep Networks.

Biomimetics (Basel, Switzerland)·2026
Same journal

A Systematic Taxonomy of the Sunflower Optimization Algorithm: Variants, Hybridization Strategies, Applications, and Research Directions.

Biomimetics (Basel, Switzerland)·2026
Same journal

Toward a Compositional Theory of Trust in Embodied Intelligence: A QNLP Framework for Modeling Context, Interaction, and Trustworthiness.

Biomimetics (Basel, Switzerland)·2026
Same journal

Empirical Logic for Bio-Inspired Soft Computing: Illustrative Applications in Control Engineering and Cluster Analysis.

Biomimetics (Basel, Switzerland)·2026
Same journal

A Modified Multi-Strategy Dhole Optimization Algorithm and Its Engineering Applications.

Biomimetics (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Jun 26, 2026

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

Reverse Mutation for Optimization Learning Artificial Lemming Algorithm and Its Application in Engineering.

Mingbin Tang1, Yejun Zheng1, Lianbao Li1

  • 1Engineering Technology Department, Shanghai Caoyang Vocational School, Shanghai 200333, China.

Biomimetics (Basel, Switzerland)
|June 25, 2026
PubMed
Summary
This summary is machine-generated.

A new Reverse Mutation for Optimization Learning Artificial Lemming Algorithm (RMALA) enhances swarm intelligence for complex engineering problems. RMALA significantly improves optimization accuracy and convergence speed, outperforming existing methods.

Keywords:
Cauchy mutationartificial lemming algorithmengineering optimizationimproved salp swarm algorithmreverse mutation for optimization learning

Related Experiment Videos

Last Updated: Jun 26, 2026

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

Area of Science:

  • Computational Intelligence
  • Optimization Algorithms
  • Engineering Applications

Background:

  • Complex engineering optimization problems are high-dimensional, multi-constraint, and nonlinear.
  • Traditional deterministic methods struggle with efficiency and accuracy.
  • Intelligent optimization algorithms are crucial for these problems.

Purpose of the Study:

  • To address limitations of the standard Artificial Lemming Algorithm (ALA), including insufficient diversity and slow convergence.
  • To propose an improved algorithm, the Reverse Mutation for Optimization Learning Artificial Lemming Algorithm (RMALA).
  • To enhance the performance of ALA for complex engineering optimization tasks.

Main Methods:

  • Integrated Cauchy mutation to maintain population diversity and prevent premature convergence.
  • Incorporated the Improved Salp Swarm Algorithm (ISSA) to boost local exploitation and accuracy.
  • Implemented reverse mutation for optimization learning to accelerate convergence and guide towards global optima.

Main Results:

  • RMALA demonstrated over 30% improvement in optimization accuracy compared to ALA on CEC2017/2022 test sets.
  • RMALA showed over 25% improvement in convergence speed.
  • RMALA exhibited superior stability and robustness against five recent swarm intelligence algorithms.

Conclusions:

  • RMALA effectively solves complex high-dimensional, nonlinear, constrained optimization problems.
  • The algorithm offers significant engineering application value and academic innovation.
  • RMALA represents a substantial advancement in intelligent optimization techniques.