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

117
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...
117
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

474
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...
474
Cluster Sampling Method01:20

Cluster Sampling Method

13.1K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
13.1K
Transformers with Off-Nominal Turns Ratios01:25

Transformers with Off-Nominal Turns Ratios

234
In scenarios involving parallel transformers with disparate ratings, developing per-unit models requires accommodating off-nominal turns ratios. This situation arises when the selected base voltages are not proportional to the transformer’s voltage ratings. Consider a transformer where the rated voltages are related by the term a. If the chosen voltage bases satisfy a relationship involving term b, term c is defined as the ratio of these bases. This ratio is then substituted into the...
234
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

791
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
791

You might also read

Related Articles

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

Sort by
Same author

An improved mountain gazelle optimizer based on chaotic map and spiral disturbance for medical feature selection.

PloS one·2024
Same author

A novel Q-learning algorithm based on improved whale optimization algorithm for path planning.

PloS one·2022
Same author

DRI-MVSNet: A depth residual inference network for multi-view stereo images.

PloS one·2022
See all related articles

Related Experiment Video

Updated: Oct 11, 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

13.1K

An improved African vultures optimization algorithm based on tent chaotic mapping and time-varying mechanism.

Jiahao Fan1,2, Ying Li1,2, Tan Wang3

  • 1College of Computer Science and Technology, Jilin University, Changchun, China.

Plos One
|November 30, 2021
PubMed
Summary

An improved African vultures optimization algorithm (AVOA) called TAVOA enhances exploration and exploitation using chaotic mapping and a time-varying mechanism. This new algorithm shows superior performance on benchmark functions and real-world engineering problems compared to existing methods.

More Related Videos

Spotting Cheetahs: Identifying Individuals by Their Footprints
09:47

Spotting Cheetahs: Identifying Individuals by Their Footprints

Published on: May 1, 2016

15.0K
Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping
07:11

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping

Published on: December 8, 2023

2.0K

Related Experiment Videos

Last Updated: Oct 11, 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

13.1K
Spotting Cheetahs: Identifying Individuals by Their Footprints
09:47

Spotting Cheetahs: Identifying Individuals by Their Footprints

Published on: May 1, 2016

15.0K
Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping
07:11

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping

Published on: December 8, 2023

2.0K

Area of Science:

  • Engineering Optimization
  • Computational Intelligence
  • Metaheuristic Algorithms

Background:

  • Metaheuristic algorithms are crucial for complex engineering problems.
  • Algorithm performance hinges on exploration and exploitation balance.
  • Existing African vultures optimization algorithm (AVOA) can be improved.

Purpose of the Study:

  • To propose an improved African vultures optimization algorithm (AVOA) named TAVOA.
  • To enhance the exploration and exploitation capabilities of the AVOA.
  • To validate the effectiveness and efficiency of TAVOA on benchmark and real-world problems.

Main Methods:

  • Introduced tent chaotic mapping for population initialization.
  • Incorporated individual historical optimal positions for location updating.
  • Developed a time-varying mechanism to balance exploration and exploitation.

Main Results:

  • TAVOA significantly outperformed AVOA on 13 of 23 basic benchmark functions.
  • TAVOA showed significant or similar performance on 26 of 28 CEC 2013 benchmark functions compared to AVOA.
  • TAVOA demonstrated competitive performance on real-world engineering design problems against six other algorithms.

Conclusions:

  • TAVOA effectively improves upon the AVOA by balancing exploration and exploitation.
  • The proposed enhancements lead to superior or comparable performance across various optimization tasks.
  • TAVOA presents a promising alternative for complex engineering optimization challenges.