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1
Application Of Genetic Algorithms For Robust Parameter Optimization
Published 2010“…Genetic algorithms (GA) are fairly recent in this respect but afford a novel method of parameter optimization. …”
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2
Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)
Published 2015“…Global optimisation is a method to identify the optimal kinetic parameter in ordinary differential equation. …”
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3
Standard equations for predicting the discharge coefficient of a modified high-performance side weir
Published 2017“…The Particle Swarm Optimization (PSO) algorithm was used to optimize the parameters of the equations. …”
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4
Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA)
Published 2024“…Acquired results which demonstrate lower values of RMSE and parameter deviation index against the standard SMA and other preceding algorithms such as particle swarm optimization, sine cosine algorithm, moth flame optimizer and ant lion optimizer ultimately verified ESMA’s efficacy as an effective approach for accurate model identification.…”
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5
Particle swarm optimization (PSO) for CNC route problem
Published 2002“…We often see many of the method of Genetic Algorithm (GA), Ant Colony Optimization (ACO), Simulated Annealing Algorithm (SAA) and PSO are used for any optimization problems. …”
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Undergraduates Project Papers -
6
Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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7
The efficiency of conjugate gradient methods with global convergence / Siti Nur Hafiza Shamsudin
Published 2019“…The global convergence result is established using exact line searches. Numerical result shows that algorithm 2 which is one of the proposed CG methods is more efficiency when compared to other algorithms.…”
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8
Thin Film Roughness Optimization In The Tin Coatings Using Genetic Algorithms
Published 2017“…In order to represent the process variables and coating roughness, a quadratic polynomial model equation was developed. Genetic algorithms were used in the optimization work of the coating process to optimize the coating roughness parameters. …”
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9
Assisted History Matching by Using Genetic Algorithm and Discrete Cosine Transform
Published 2014“…Later, an algorithm combining both Genetic Algorithm and Discrete Cosine Transform was proposed, which shows the step-by-step sequence of both methods. …”
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Final Year Project -
10
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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Sliding Mode Controller Design With Optimized PID Sliding Surface Using Particle Swarm Algorithm
Published 2017“…In the performance assessment on the designed PID sliding surface, the controller parameter is first obtained through conventional tuning method known as Ziegler-Nichols (ZN), which is then compared with the particle swarm optimization (PSO) computational tuning algorithm. …”
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13
Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin
Published 2014“…A MySQL database was created to analyze the optimization results and speed up computations of the optimization algorithm. …”
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14
Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy
Published 2024“…Anchored in mathematical modelling using ordinary differential equations (ODE), the study culminates in a Multi-Objective Optimal Control Problem (MOCP), categorizing into Pure MOCP (P-MOCP) and Hybrid MOCP (H-MOCP). …”
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15
Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Published 2021“…In this research, a novel algorithm (Herschel Bulkley Network) is introduced to simulate the non-Newtonian fluid flow in a pipe using data redundant deep neural network (DNN) for fully developed, laminar, and incompressible flow conditions. …”
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16
A novel explanatory hybrid artificial bee colony algorithm for numerical function optimization
Published 2020“…However, it is impossible to fnd an optimization algorithm that can obtain the global optimum for every optimization problem. …”
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17
Parameter estimation of stochastic differential equation
Published 2012“…The results showed that the Mean Square Errors (MSE) for stochastic model with parameters estimated using optimal knot for 1,000, 5,000 and 10,000 runs of Brownian motions are smaller than the SDE models with estimated parameters using knot selected heuristically. …”
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PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah
Published 2017“…Typically, parameter estimation is performed using various types of Least Squares (LS) algorithms due to its stable and efficient numerical computation. …”
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19
Eccentricity Optimization of NGB System by using Multi-Objective Genetic Algorithm
Published 2009“…In this study, a new method for designing a particular braced system by using multi-objective genetic algorithm is proposed. …”
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Modeling And Optimization Of Physical Vapour Deposition Coating Process Parameters For Tin Grain Size Using Combined Genetic Algorithms With Response Surface Methodology
Published 2015“…Optimization of thin film coating parameters is important in identifying the required output.Two main issues of the process of physical vapor deposition (PVD) are manufacturing costs and customization of cutting tool properties.The aim of this study is to identify optimal PVD coating process parameters.Three process parameters were selected, namely nitrogen gas pressure (N2),argon gas pressure (Ar),and Turntable Speed (TT),while thin film grain size of titanium nitrite (TiN) was selected as an output response.Coating grain size was characterized using Atomic Force Microscopy (AFM) equipment.In this paper,to obtain a proper output result,an approach in modeling surface grain size of Titanium Nitrite (TiN)coating using Response Surface Method (RSM) has been implemented. …”
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