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Views
Date
Relevance
Potential Scenario
173
views
53
downloads
0
comments
2017-Sim-EtAl-Optimal control of a coupled tanks system with model-reality differences
In this paper, an efficient computational approach is proposed to optimize and control a coupled tanks system.
optimal control
flow
tanks
coupled tanks
Potential Scenario
167
views
90
downloads
0
comments
2018-Akman-EtAl-Parameter Estimation in Ordinary Differential Equations Modeling via Particle Swarm Optimization
We demonstrate Particle Swarm Optimization efficacy by showing that it outstrips evolutionary computing methods previously used to analyze an epidemic model.
epidemic
Particle Swarm Optimization
optimize parameters
Modeling Scenario
403
views
506
downloads
0
comments
1-047a-CondensationOptimization-ModelingScenario
We seek to optimize a condensation process which is modeled by a simulation using the random motion of 200 particles in a 50 by 50 square in which a particle bounces off the two vertical and top walls and condenses on the bottom wall.
simulation
data
optimization
energy
condensation
best fit
cost
sum of scquare errors
Potential Scenario
209
views
93
downloads
0
comments
2014-Enderling-Chaplain-Mathematical Modeling of Tumor Growth and Treatment
Herein we describe fundamentals of mathematical modeling of tumor growth and tumor-host interactions, and summarize some of the seminal and most prominent approaches.
cancer
tumor modeling
angiogenesis
tumor growth
patient care
Potential Scenario
144
views
59
downloads
0
comments
2017-Agmour-EtAl-Optimization of the Two Fishermen's Profits Exploiting Three Competing Species Where Prices Depend on Harvest
The main purpose of this work is to define the fishing effort that maximizes the profit of each fisherman, but all of them have to respect two constraints: the first one is the sustainable management of the resources and the second one is...
Fishing
harvest
Nash equilibrium
optimize
profits
Potential Scenario
141
views
48
downloads
0
comments
2012-Nokkaew-EtAl-Estimation of Algae Growth Model Parameters by a Double Layer Genetic Algorithm
This paper presents a double layer genetic algorithm (DLGA) to improve performance of the information-constrained parameter estimations.
optimization
algae growth
genetic algorithms
simulated data
convergence of parameters
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