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

Wald-Wolfowitz Runs Test I01:17

Wald-Wolfowitz Runs Test I

724
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...
724
Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

59.3K
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).
59.3K
Genetic Drift03:33

Genetic Drift

40.5K
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.
40.5K
Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

303
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...
303
Randomized Experiments01:13

Randomized Experiments

7.1K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
7.1K
Genetics of Speciation02:16

Genetics of Speciation

19.5K
Speciation is the evolutionary process resulting in the formation of new, distinct species—groups of reproductively isolated populations.
19.5K

You might also read

Related Articles

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

Sort by
Same author

Regional frequency analysis of extreme wind in Pakistan using robust estimation methods.

Scientific reports·2024
Same author

Rising food prices and poverty in Pakistan.

PloS one·2023
Same author

A Novel Selection Approach for Genetic Algorithms for Global Optimization of Multimodal Continuous Functions.

Computational intelligence and neuroscience·2019
Same author

Genetic Algorithm for Traveling Salesman Problem with Modified Cycle Crossover Operator.

Computational intelligence and neuroscience·2017
Same journal

Analysis of strength degradation of coal and rock masses and stability of mined areas under long term immersion environment.

PloS one·2026
Same journal

Biogenic Silver-Selenium nanocomposite with anticancer activity and potent efficacy against vancomycin-resistant Staphylococcus aureus.

PloS one·2026
Same journal

Preparation and physicochemical characterization of a biodegradable chitosan/carboxymethyl cellulose hydrogel synthesized in NaOH/urea medium.

PloS one·2026
Same journal

Action-guilt, survivor-guilt, and depression in combat-related PTSD.

PloS one·2026
Same journal

Explainable machine learning for predicting activities of daily living at discharge in stroke patients: A retrospective study using SHAP interpretability.

PloS one·2026
Same journal

Deep learning based two-way feature depiction model for brain tumor detection.

PloS one·2026
See all related articles

Related Experiment Video

Updated: Aug 29, 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

11.8K

Genetic algorithm with a new round-robin based tournament selection: Statistical properties analysis.

Abid Hussain1, Salma Riaz2, Muhammad Sohail Amjad3

  • 1Department of Statistics, Govt. College Khayaban-e-Sir Syed, Rawalpindi, Pakistan.

Plos One
|September 9, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a novel round-robin tournament selection operator for genetic algorithms (GAs). The new operator enhances selection pressure and sampling accuracy while maintaining population diversity, improving overall performance on complex problems like the Traveling Salesman Problem.

More Related Videos

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

7.6K
Digital PCR-based Competitive Index for High-throughput Analysis of Fitness in Salmonella
07:11

Digital PCR-based Competitive Index for High-throughput Analysis of Fitness in Salmonella

Published on: May 13, 2019

9.7K

Related Experiment Videos

Last Updated: Aug 29, 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

11.8K
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

7.6K
Digital PCR-based Competitive Index for High-throughput Analysis of Fitness in Salmonella
07:11

Digital PCR-based Competitive Index for High-throughput Analysis of Fitness in Salmonella

Published on: May 13, 2019

9.7K

Area of Science:

  • Computational Intelligence
  • Optimization Algorithms
  • Evolutionary Computation

Background:

  • Genetic algorithms (GAs) are powerful optimization tools.
  • Effective selection operators are crucial for GA performance.
  • Existing selection methods can sometimes lead to premature convergence or loss of diversity.

Purpose of the Study:

  • To propose a novel round-robin tournament selection operator for genetic algorithms.
  • To evaluate the selection pressure and population diversity of the new operator.
  • To assess the impact of the new operator on sampling accuracy and global performance.

Main Methods:

  • A round-robin tournament selection strategy was developed, dividing the population into two competing groups.
  • Pearson's chi-square and empirical distribution function were used for statistical property analysis.
  • The Traveling Salesman Problem was employed to measure the efficiency of the new selection scheme.

Main Results:

  • The proposed operator demonstrated improved selection pressure with minimal loss of population diversity.
  • Sampling accuracy was enhanced at the cost of a nominal increase in complexity.
  • The new selection scheme showed improved performance on the Traveling Salesman Problem compared to existing operators.

Conclusions:

  • The round-robin tournament selection operator is an effective addition to genetic algorithms.
  • It offers a favorable balance between selection pressure and diversity maintenance.
  • The operator shows promise for improving the efficiency of GAs in solving complex optimization problems.