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

Response Surface Methodology01:16

Response Surface Methodology

367
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:
367
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

158
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...
158
Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

2.0K
Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
2.0K
Principle of Linear Impulse and Momentum for a Single Particle: Problem Solving01:23

Principle of Linear Impulse and Momentum for a Single Particle: Problem Solving

760
Consider a wooden box and a cylinder of known masses m1 and m2, respectively,  hanging from a ceiling with the help of a massless pulley system.
760
Newtonian Fluid: Problem Solving01:18

Newtonian Fluid: Problem Solving

620
Newtonian fluids exhibit a constant viscosity, meaning their shear stress and shear strain rate are directly proportional. This property ensures a predictable and stable response to applied forces, maintaining a linear relationship between force and flow. Examples include water, air, and light oils, consistently demonstrating this proportional behavior regardless of external conditions.
A velocity gradient forms within the fluid when a Newtonian fluid is placed between two parallel plates, with...
620
Three-Dimensional Force System:Problem Solving01:30

Three-Dimensional Force System:Problem Solving

1.1K
A three-dimensional force system refers to a scenario in which three forces act simultaneously in three different directions. This type of problem is commonly encountered in physics and engineering, where it is necessary to calculate the resultant force on the system, which can then be used to predict or analyze the behavior of the object or structure under consideration.
To solve a three-dimensional force system, first resolve each force into its respective scalar components. Do this using...
1.1K

You might also read

Related Articles

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

Sort by
Same author

Integrated use of chemical and geophysical monitoring to study the diesel oil biodegradation in microcosms with different operative conditions.

Journal of environmental health science & engineering·2021
Same author

Open-Ended Coaxial Probe Measurements of Complex Dielectric Permittivity in Diesel-Contaminated Soil during Bioremediation.

Sensors (Basel, Switzerland)·2020
Same author

Laboratory Testing of FBGs for Pipeline Monitoring.

Sensors (Basel, Switzerland)·2020
Same author

SEIR Modeling of the Italian Epidemic of SARS-CoV-2 Using Computational Swarm Intelligence.

International journal of environmental research and public health·2020
Same journal

A Review of Electromagnetic Induction on Planetary Bodies.

Surveys in geophysics·2026
Same journal

Assessment of Atmospheric and Surface Energy Budgets Using Observation-Based Data Products.

Surveys in geophysics·2024
Same journal

An Abrupt Decline in Global Terrestrial Water Storage and Its Relationship with Sea Level Change.

Surveys in geophysics·2024
Same journal

Closure of Earth's Global Seasonal Cycle of Energy Storage.

Surveys in geophysics·2024
Same journal

Observational Assessment of Changes in Earth's Energy Imbalance Since 2000.

Surveys in geophysics·2024
Same journal

North Atlantic Heat Transport Convergence Derived from a Regional Energy Budget Using Different Ocean Heat Content Estimates.

Surveys in geophysics·2024
See all related articles

Related Experiment Video

Updated: Nov 8, 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

13.2K

A Review of Geophysical Modeling Based on Particle Swarm Optimization.

Francesca Pace1, Alessandro Santilano2, Alberto Godio1

  • 1Department of Environment, Land and Infrastructure Engineering (DIATI), Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy.

Surveys in Geophysics
|April 19, 2021
PubMed
Summary
This summary is machine-generated.

Particle Swarm Optimization (PSO) effectively models Earth's subsurface using geophysical data. This review analyzes PSO

Keywords:
InversionJoint optimizationOptimizationParticle swarm optimizationStochastic inverse modelingSwarm intelligence

More Related Videos

Open-source Single-particle Analysis for Super-resolution Microscopy with VirusMapper
07:38

Open-source Single-particle Analysis for Super-resolution Microscopy with VirusMapper

Published on: April 9, 2017

10.3K
A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
13:54

A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM

Published on: August 18, 2023

5.3K

Related Experiment Videos

Last Updated: Nov 8, 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

13.2K
Open-source Single-particle Analysis for Super-resolution Microscopy with VirusMapper
07:38

Open-source Single-particle Analysis for Super-resolution Microscopy with VirusMapper

Published on: April 9, 2017

10.3K
A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
13:54

A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM

Published on: August 18, 2023

5.3K

Area of Science:

  • Geophysics
  • Computational Science

Background:

  • Geophysical data interpretation often requires complex inverse modeling.
  • Stochastic methods are crucial for handling uncertainties in subsurface models.

Purpose of the Study:

  • To review the application of Particle Swarm Optimization (PSO) for stochastic inverse modeling of geophysical data.
  • To analyze the evolution, benefits, and limitations of PSO methodologies in geophysics.

Main Methods:

  • Literature review of PSO applications in geophysical inverse modeling.
  • Analysis of case studies across various geophysical data types (electromagnetic, gravity, magnetic, seismic, etc.).
  • Examination of multi-objective PSO for joint inversion of multiple datasets.

Main Results:

  • PSO has been successfully applied to diverse geophysical inverse problems.
  • Multi-objective PSO offers advantages in handling conflicting objectives in joint inversions.
  • Critical evaluation highlights both strengths and weaknesses of current PSO approaches.

Conclusions:

  • PSO is a valuable tool for stochastic inverse modeling in geophysics.
  • Best practices for implementing custom PSO algorithms are proposed.
  • Further research can refine PSO for enhanced subsurface characterization.