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

98
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...
98
Woodward–Hoffmann Selection Rules and Microscopic Reversibility01:34

Woodward–Hoffmann Selection Rules and Microscopic Reversibility

3.2K
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...
3.2K
Area Computation by the Alternative Coordinate Method01:24

Area Computation by the Alternative Coordinate Method

131
The alternative coordinate method, also known as the Shoelace Formula, is a technique for determining the area of a traverse using Cartesian coordinates. This method relies on the sequential arrangement of x and y coordinates for each point of the shape, ensuring accuracy and ease of application.In this approach, each corner's x and y coordinates are listed as fractions, with the x-coordinate as the numerator and the y-coordinate as the denominator. These coordinates are arranged sequentially...
131
Areas Within Irregular Boundaries01:26

Areas Within Irregular Boundaries

108
Calculating areas within irregular boundaries, such as along rivers or curved roads, is crucial in various fields, including surveying, engineering, and environmental management. Surveyors often begin by creating a traverse, a connected series of straight lines approximating the area's boundary. The coordinates of each traverse point are essential for calculating the enclosed area. The double meridian distance formula is a widely used technique for this purpose. This method utilizes the...
108
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

114
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
114
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

267
The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
267

You might also read

Related Articles

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

Sort by
Same author

An enhancing framework with an emphasis on decision balance in ensemble regression.

Neural networks : the official journal of the International Neural Network Society·2026
Same author

Multi-Objective Drug Molecule Optimization Based on Tanimoto Crowding Distance and Acceptance Probability.

Pharmaceuticals (Basel, Switzerland)·2025
Same author

Molecular Optimization Based on a Monte Carlo Tree Search and Multiobjective Genetic Algorithm.

Journal of chemical information and modeling·2025
Same author

A Many-Objective Evolutionary Algorithm Based on Dual Selection Strategy.

Entropy (Basel, Switzerland)·2023
Same author

An Orthogonal Evolutionary Algorithm With Learning Automata for Multiobjective Optimization.

IEEE transactions on cybernetics·2015
Same author

Artificial Bee Colony Algorithm Based on Information Learning.

IEEE transactions on cybernetics·2015
Same journal

Turbulent flow in a vortex separator with a directed pipe inlet.

Scientific reports·2026
Same journal

Systematic characteristic evaluation of clay-based cementitious material derived from calcium carbide residue and waste tile powder.

Scientific reports·2026
Same journal

Retraction Note: Improvement of a rapid diagnostic application of monoclonal antibodies against avian influenza H7 subtype virus using Europium nanoparticles.

Scientific reports·2026
Same journal

Applying large language models to spam detection in the Kazakh low-resource language setting.

Scientific reports·2026
Same journal

An open-source 3D printing system enabling in-situ freeze-thaw processing of hydrogels.

Scientific reports·2026
Same journal

An enhanced EfficientNet framework for automated waste classification using cosine annealing and label smoothing.

Scientific reports·2026
See all related articles

Related Experiment Video

Updated: Aug 20, 2025

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

Fast prototype selection algorithm based on adjacent neighbourhood and boundary approximation.

Juan Li1, Cai Dai2

  • 1College of Distance Education, Shaanxi Normal University, Xi'an, 710062, Shaanxi, China.

Scientific Reports
|November 23, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a new prototype selection algorithm for large datasets. It efficiently creates a smaller, high-quality reference set for incremental learning without sacrificing accuracy.

More Related Videos

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
12:11

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

8.3K
Topographical Estimation of Visual Population Receptive Fields by fMRI
06:02

Topographical Estimation of Visual Population Receptive Fields by fMRI

Published on: February 3, 2015

9.3K

Related Experiment Videos

Last Updated: Aug 20, 2025

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
Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
12:11

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

8.3K
Topographical Estimation of Visual Population Receptive Fields by fMRI
06:02

Topographical Estimation of Visual Population Receptive Fields by fMRI

Published on: February 3, 2015

9.3K

Area of Science:

  • Machine Learning
  • Data Mining
  • Computer Science

Background:

  • Increasing data volumes challenge traditional classification algorithms.
  • Existing methods struggle with execution time and memory constraints in incremental environments.

Purpose of the Study:

  • To develop a novel prototype selection algorithm for efficient incremental learning.
  • To address the need for fast, adaptive reference set generation in large datasets.

Main Methods:

  • Integrates condensing and editing strategies for prototype selection.
  • Extends neighbor reference from single to k-nearest neighborhood.
  • Uses neighbor relationships and classification boundaries to identify prototypes.
  • Periodically updates prototypes in non-boundary or unlearned zones.

Main Results:

  • Achieves a smaller reference set with higher boundary prototypes.
  • Maintains classification accuracy and reduction rate compared to existing algorithms.
  • Demonstrates effectiveness in handling incremental data environments and large datasets.

Conclusions:

  • The proposed algorithm offers an efficient solution for large-scale incremental learning.
  • It effectively balances reference set size, accuracy, and adaptability.
  • Provides a valuable tool for applications requiring dynamic data processing.