Search Results - (( variable equations using algorithm ) OR ( using optimization method algorithm ))
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Optimization of biochemical systems production using combination of newton method and particle swarm optimization
Published 2019“…In the proposed method, the Newton method was used to deal with nonlinear equations system, while the PSO algorithm was utilized to fine-tune the variables in nonlinear equations system. …”
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Taguchi?s T-method with Normalization-Based Binary Bat Algorithm
Published 2025“…Therefore, a variable selection technique using a swarm-based Binary Bat algorithm is proposed. …”
Conference paper -
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Modification of particle swarm optimization algorithm for optimization of discrete values
Published 2011“…We propose a novel modification to the PSO algorithm to perform rapid discrete optimization. The proposed Discrete-PSO method (DPSO) uses a rescaling equation to convert the continuous-valued positions into discrete-valued variables. …”
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Research Reports -
4
A Hybrid of Optimization Method for Multi-Objective Constraint Optimization of Biochemical System Production
Published 2015“…Then, Genetic Algorithm (GA) in SPEA and CCA were used to represent the variables in non-linear equations system into multiple sub-chromosomes. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. …”
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Thesis -
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Comparative study of modified BFGS and new scale modified BFGS for solving unconstrained optimization / Shahirah Atikah Mohamad Husnin
Published 2018“…Broyden-Fletcher-Goldfarb-Shanno (BFGS) is one of a well-known Quasi-Newton update formula. This method is generally considered as the most efficient method among other variable metric methods for solving unconstrained optimization problems. …”
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Thesis -
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The efficiency of conjugate gradient methods with global convergence / Siti Nur Hafiza Shamsudin
Published 2019“…Conjugate gradient methods are usually used to solve any problem that related to large number of variables such as a large linear system of equations. …”
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Thesis -
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Multi-objective Optimization of Biochemical System Production Using an Improve Newton Competitive Differential Evolution Method
Published 2017“…Then DE and ComCA are used to represent the variables in nonlinear equation system and tune the variables in order to find the best solution. …”
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Partial Newton methods for a system of equations
Published 2013“…But the proposed partial Newton iteration makes it significantly simpler and faster to compute in each iteration for a system of equations with many variables. This is because it uses only one or two variables instead of all the search variables in each iteration.…”
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Thin Film Roughness Optimization In The Tin Coatings Using Genetic Algorithms
Published 2017“…Genetic algorithms were used in the optimization work of the coating process to optimize the coating roughness parameters. …”
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OPTIMIZATION OF DESIGN PARAMETERS FOR A VARIABLE FREQUENCY 3-PHASE INDUCTION MOTOR
Published 2009“…This report describes the method of optimizing a variable frequency 3-phase Induction Motor. …”
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Final Year Project -
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Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak
Published 2025“…A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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Thesis -
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Implementation of simulated annealing for two variables non-linear function
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Working Paper -
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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“…Additionally,analysis of variance(ANOVA) was used to determine the significant factors influencing resultant TiN coating grain size.Based on that,a quadratic polynomial model equation was developed to represent the process variables and coating grain size.Then,in order to optimize the coating process parameters, genetic algorithms (GAs) were combined with the RSM quadratic model and used for optimization work.Finally,the models were validated using actual testing data to measure model performances in terms of residual error and prediction interval (PI).The result indicated that for RSM,the actual coating grain size of validation runs data fell within the 95% (PI) and the residual errors were less than 10 nm with very low values, the prediction accuracy of the model is 96.09%.In terms of optimization and reduction the experimental data,GAs could get the best lowest value for grain size then RSM with reduction ratio of ≈6%, ≈5%, respectively.…”
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Numerical methods for nonlinear optimal control problems using haar wavelet operational matrices / Waleeda Swaidan Ali
Published 2015“…This thesis is based on solving optimal control problems by using both direct and indirect methods. …”
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Thesis -
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Deterministic Mutation Algorithm As A Winner Over Forward Selection Procedure
Published 2016“…A parsimonious model structure is desirable in enabling easy control design. Two methods of model structure selection are closely looked into and these are deterministic mutation algorithm (DMA) and forward selection procedure (FSP). …”
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Article -
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Power System State Estimation In Large-Scale Networks
Published 2010“…The Weighted Least Squares (WLS) method is the most popular technique of SE. This thesis provides solutions to enhance the WLS algorithm in order to increase the performance of SE. …”
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Thesis -
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Numerical study on natural convection in inclined enclosures with non-uniform boundary conditions / Cheong Huey Tyng
Published 2013“…The governing system of partial differential equations are non- dimensionalized using the suitable dimensionless variables. …”
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