Search Results - (( variable exploration techniques algorithm ) OR ( parameter optimization based algorithm ))
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1
Fuzzy Adaptive Tuning of a Particle Swarm Optimization Algorithm for Variable-Strength Combinatorial Test Suite Generation
Published 2018“…Research has shown that stochastic population-based algorithms such as particle swarm optimization (PSO) can be efficient compared to alternatives for VS-CIT problems. …”
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Book Chapter -
2
Fuzzy modelling and control for a nonlinear reboiler system of a distillation column
Published 2006“…Genetic algorithm (GA) is used to tune the parameters of the Fuzzy controller. …”
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Thesis -
3
Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment
Published 2017“…The proposed strategy is dependent on modified Zimmermanns approach for handling all inexact operating costs, data capacities, and demand variables. The SD algorithm is employed to balance exploitation and exploration in MSA, thereby resulting in efficient and effective (speed and quality) solution for the APP model. …”
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4
Model input and structure selection in multivariable dynamic modeling of batch distillation column pilot plant / Ilham Rustam
Published 2015“…Comparison results have shown that the pre-screening method has an essential role in determining an effective process representation especially in real-time multivariable identification framework where a priori knowledge is not available and would help in resultant model generalization performance as opposed to simply using all available model input variables. Further, after a careful investigation into the OLS algorithm, it was shown that the ERR technique which is an essential part of the algorithm to reach model parsimony, has led the resultant model to select an incorrect model terms albeit some improvement in model selection criteria and validation method adopted in this study. …”
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Thesis -
5
Modeling of flood water level prediction using NNARX / Fazlina Ahmat Ruslan
Published 2015“…Comparison results have shown that the pre-screening method has an essential role in determining an effective process representation especially in real-time multivariable identification framework where a priori knowledge is not available and would help in resultant model generalization performance as opposed to simply using all available model input variables. Further, after a careful investigation into the OLS algorithm, it was shown that the ERR technique which is an essential part of the algorithm to reach model parsimony, has led the resultant model to select an incorrect model terms albeit some improvement in model selection criteria and validation method adopted in this study. …”
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Thesis -
6
Operational matrix based on orthogonal polynomials and artificial neural networks methods for solving fractal-fractional differential equations
Published 2024“…Our OM techniques based on SLPs and SJPs require only a few terms to obtain an accurate solution. …”
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7
Multi-objective optimization of process variables for MWCNT-added electro-discharge machining of 316L steel
Published 2021“…The best 21 solution sets predicted through the multi-objective optimization tool called non-dominated sorting genetic algorithm-II (NSGA-II) obeying the set objective functions are proposed which are obtained from the Pareto optimal frontiers. …”
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Article -
8
Multi-objective optimization of process variables for MWCNT-added electro-discharge machining of 316L steel
Published 2021“…The best 21 solution sets predicted through the multi-objective optimization tool called non-dominated sorting genetic algorithm-II (NSGA-II) obeying the set objective functions are proposed which are obtained from the Pareto optimal frontiers. …”
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Article -
9
Optimum Design of PIλDμ Controller for an Automatic Voltage Regulator System Using Combinatorial Test Design
Published 2016“…This significantly reduced the number of tests needed and thus leads to an approach that optimizes design of parameters quickly.…”
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10
Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems
Published 2011“…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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Thesis -
11
On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing
Published 2015“…In doing so, this paper reviews two existing parameter free optimization algorithms involving Teaching Learning Based Optimization (TLBO) and Fruitfly Optimization Algorithm (FOA) in an effort to promote their adoption for CIT.…”
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Article -
12
Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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13
Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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14
LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting
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Conference or Workshop Item -
15
Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri
Published 2020“…Based on the capabilities of the metaheuristic algorithms, this research is proposing the enhanced Gravitational Search Algorithm (eGSA) to solve the nano-process parameter optimization problem. …”
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Thesis -
16
Optimization of turning parameters using genetic algorithm method
Published 2008“…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
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Undergraduates Project Papers -
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Optimization of milling parameters using ant colony optimization
Published 2008“…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
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Undergraduates Project Papers -
18
Improvement of horizontal streak on disparity map thru parameter optimization for stereo vision algorithm
Published 2024“…Then, the research continues to optimize the proposed local based SVDM algorithm through parameters optimization in obtaining the final disparity map. …”
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Article -
19
Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…—Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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20
Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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