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

100
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...
100
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

695
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...
695
Response Surface Methodology01:16

Response Surface Methodology

250
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
250
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

136
Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
136
Decision Making: P-value Method01:09

Decision Making: P-value Method

5.6K
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
5.6K
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

147
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
147

You might also read

Related Articles

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

Sort by
Same author

Regenerative Polysulfide-Scavenging Layers Enabling Lithium-Sulfur Batteries with High Energy Density and Prolonged Cycling Life.

ACS nano·2017
Same author

PdAuCu Nanobranch as Self-Repairing Electrocatalyst for Oxygen Reduction Reaction.

ChemSusChem·2017
Same author

Trapdoor spiders of the genus <i>Cyclocosmia</i> Ausserer, 1871 from China and Vietnam (Araneae, Ctenizidae).

ZooKeys·2017
Same author

The complete genome sequence, occurrence and host range of Tomato mottle mosaic virus Chinese isolate.

Virology journal·2017
Same author

Tunneling nanotubes promote intercellular mitochondria transfer followed by increased invasiveness in bladder cancer cells.

Oncotarget·2017
Same author

Assessment of histopathological features of needle biopsy in recurrent prostate cancer following salvage high-intensity focused ultrasound.

Canadian Urological Association journal = Journal de l'Association des urologues du Canada·2017
Same journal

Relaxed Stability Conditions for Model Predictive Control of Hybrid Dynamical Systems Using Hybrid Recurrent Neural Networks.

IEEE transactions on cybernetics·2026
Same journal

An Evolutionary Algorithm Assisted by an Ensemble of Pareto-Optimal Surrogate Models.

IEEE transactions on cybernetics·2026
Same journal

A Quantum Self-Attention Neural Network Model on Quantum Circuits.

IEEE transactions on cybernetics·2026
Same journal

Semi-Explicit Solution of Some Discrete-Time Higher-Order-Cost Mean-Field-Type Control.

IEEE transactions on cybernetics·2026
Same journal

A Novel One-Step Small Object Detector for Autonomous Aerial Vehicles.

IEEE transactions on cybernetics·2026
Same journal

Online Data-Driven-Based Optimal Output Tracking Control Without Initial Stabilizing Policy.

IEEE transactions on cybernetics·2026
See all related articles

Related Experiment Video

Updated: Sep 4, 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

Surrogate-Assisted Multi-Objective Evolutionary Optimization With Pareto Front Model-Based Local Search Method.

Fan Li, Liang Gao, Weiming Shen

    IEEE Transactions on Cybernetics
    |July 15, 2022
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel Pareto front (PF) model-based local search method to enhance multi-objective evolutionary algorithms. The method accelerates convergence towards the true Pareto front by intelligently guiding the search using a predicted PF model.

    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

    11.8K
    Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
    10:58

    Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

    Published on: July 25, 2013

    17.1K

    Related Experiment Videos

    Last Updated: Sep 4, 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

    11.8K
    Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
    10:58

    Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

    Published on: July 25, 2013

    17.1K

    Area of Science:

    • Computational Intelligence
    • Optimization Algorithms
    • Multi-Objective Evolutionary Algorithms

    Background:

    • Surrogate-assisted multi-objective evolutionary algorithms (MOEAs) aim to accelerate convergence to the Pareto front (PF).
    • Existing local search methods can be integrated into MOEAs to improve search efficiency.
    • Effective exploration and exploitation of the PF are crucial for MOEA performance.

    Purpose of the Study:

    • To propose a novel Pareto front (PF) model-based local search method.
    • To accelerate both the exploration and exploitation phases of the PF in MOEAs.
    • To improve the efficiency and superiority of surrogate-assisted MOEAs.

    Main Methods:

    • A predicted PF model is constructed using current non-dominated solutions.
    • Sparse points from the predicted PF guide local search directions, focusing on promising areas.
    • Optima of surrogate models are used to accelerate the discovery of extreme points on the PF.

    Main Results:

    • The proposed local search method effectively accelerates the search towards the real PF.
    • The integration of the method into a surrogate-assisted MOEA demonstrated significant efficiency.
    • Experimental results on ZDT, DTLZ, and MAF instances confirmed the algorithm's superiority.

    Conclusions:

    • The proposed PF model-based local search method enhances the performance of surrogate-assisted MOEAs.
    • The approach effectively balances exploration and exploitation for faster convergence to the PF.
    • The method shows promise for improving optimization in complex multi-objective problems.