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

56
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...
56
Heuristics01:21

Heuristics

93
Heuristics are problem-solving strategies that use mental shortcuts to simplify decision-making. Unlike algorithms, which must be followed precisely to achieve a correct result, heuristics offer a general problem-solving framework. They save time and energy but can sometimes lead to less rational decisions.
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...
93
Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

244
The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and...
244
Wald-Wolfowitz Runs Test I01:17

Wald-Wolfowitz Runs Test I

650
The Wald-Wolfowitz test, also known as the runs test, is a nonparametric statistical test used to assess the randomness of a sequence of two different types of elements (e.g., positive/negative values, successes/failures). It examines whether the order of the elements in a sequence is random or if there is a pattern or trend present. This nonparametric test applies to any ordered data despite the population and sample data distribution, even if a higher sample size is available.
The test works...
650
Routh-Hurwitz Criterion II01:19

Routh-Hurwitz Criterion II

256
In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first...
256
Statically Indeterminate Problem Solving01:16

Statically Indeterminate Problem Solving

381
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...
381

You might also read

Related Articles

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

Sort by
Same author

Machine Learning-Guided Pore Engineering of Metal-Organic Frameworks for Ultrahigh Volumetric Methane Storage.

Journal of the American Chemical Society·2026
Same author

A Heterometallic Metal-Organic Framework with Atomically Precise Single-Cu Sites for Photocatalysis.

Journal of the American Chemical Society·2026
Same author

Impact of anti-Müllerian hormone on pregnancy outcomes in in vitro maturation: a retrospective cohort study.

Journal of ovarian research·2026
Same author

Donor sperm IVF pregnancies exhibit elevated risk of new-onset hypertensive disorders: a retrospective cohort study.

Journal of assisted reproduction and genetics·2026
Same author

Structural Engineering of a Zn<sub>4</sub>O-Based Metal-Organic Framework via Geometric Deformation of Secondary Building Units for Enhanced Trace Benzene Adsorption.

Inorganic chemistry·2026
Same author

Electrocatalytic Semi-Hydrogenation of Pyridine Derivatives over an In Situ Assembled Cu Cathode.

Journal of the American Chemical Society·2025

Related Experiment Video

Updated: Jul 7, 2025

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

13.0K

A hybrid algorithm of grey wolf optimizer and harris hawks optimization for solving global optimization problems with

Binbin Tu1, Fei Wang2, Yan Huo3

  • 1College of Intelligent Science and Engineering, Shenyang University, Shenyang, China.

Scientific Reports
|December 21, 2023
PubMed
Summary

A new hybrid grey wolf optimizer (HGWO) enhances population diversity and convergence speed. This improved algorithm excels in global exploration and local exploitation, proving effective for complex engineering problems.

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

11.7K
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

Related Experiment Videos

Last Updated: Jul 7, 2025

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

13.0K
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

11.7K
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

Area of Science:

  • Computational Intelligence
  • Meta-heuristic Optimization Algorithms

Background:

  • The Grey Wolf Optimizer (GWO) is a popular meta-heuristic algorithm.
  • GWO suffers from limited population diversity, premature convergence to local optima, and slow convergence rates.

Purpose of the Study:

  • To introduce a Hybrid Grey Wolf Optimizer (HGWO) to overcome GWO's limitations.
  • To enhance exploration and exploitation capabilities for improved optimization performance.

Main Methods:

  • HGWO integrates the exploitation phase of Harris Hawk Optimization (HHO).
  • Employs Latin hypercube sampling for population initialization.
  • Incorporates a nonlinear convergence factor with local perturbations and extended exploration strategies.
  • Utilizes a greedy approach for position updates.

Main Results:

  • HGWO demonstrates superior global exploration and local exploitation abilities.
  • The algorithm shows improved convergence speed and accuracy compared to GWO and other variants.
  • Evaluated using 23 benchmark functions and CEC2020, HGWO outperformed existing methods.

Conclusions:

  • The proposed HGWO effectively addresses the weaknesses of the standard GWO.
  • HGWO exhibits significant advantages in solving complex engineering problems, validating its effectiveness and applicability.