Related Experiment Video

Updated: Jul 15, 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

Golf Optimization Algorithm: A New Game-Based Metaheuristic Algorithm and Its Application to Energy Commitment

Zeinab Montazeri1, Taher Niknam1, Jamshid Aghaei2

  • 1Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz 7155713876, Iran.

Biomimetics (Basel, Switzerland)
|September 27, 2023
PubMed
Abstract

Keywords:
energyenergy carriersexploitationexplorationgame-basedgolfmetaheuristic algorithmoptimizationreal-world applicationsresilience

More Related Videos

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

591
A Quantitative Fitness Analysis Workflow11:39

A Quantitative Fitness Analysis Workflow

Published on: August 13, 2012

14.5K

Related Concept Videos

Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
63
Optimal Foraging00:48

Optimal Foraging

How animals obtain and eat their food is called foraging behavior. Foraging can include searching for plants and hunting for prey and depends on the species and environment.
12.1K
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
666
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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...
72
Coping Strategies: Problem Focused01:27

Coping Strategies: Problem Focused

Coping strategies are methods people use to manage, tolerate, or reduce the effects of stressors. These strategies involve both behavioral and psychological actions to handle stressful situations. One common approach is problem-focused coping, which aims to change or eliminate the source of stress rather than merely addressing its consequences. This method involves taking direct action to resolve the issue causing stress.
For example, consider a student who struggles to understand their...
92
Response Surface Methodology01:16

Response Surface Methodology

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:
171