Search Results - (( parameter optimisation based algorithm ) OR ( based validation using algorithm ))
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NARX modelling for steam distillation pilot plant using binary particle swarm optimisation technique / Najidah Hambali
Published 2019“…The proposed NARX-based BPSO algorithm was implemented for both time-varying water and steam temperature from the SDPP. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Dynamic modelling of a flexible beam structure using feedforward neural networks for active vibration control
Published 2019“…A non-parametric modelling approach of the system was proposed based on feed-forward neural networks (FNNs) while its weight and bias parameters were optimised using chaotic-enhanced stochastic fractal search (SFS) algorithm. …”
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Development of soft computing prediction model for the influent physicochemical characteristics of sewage treatment plants / Mozafar Ansari
Published 2021“…The best algorithm for each parameter was selected based on these criteria. …”
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Energy and Cost Integration for Multi-Objective Optimisation in a Sustainable Turning Process
Published 2018“…The multi-objective optimisation using Response Surface Methodology (RSM) was compared with the Non-Sorted Genetic Algorithm II (NSGA II) before experimental confirmation tests were made. …”
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Efficient task scheduling strategies using symbiotic organisms search algorithm for cloud computing environment
Published 2022“…The SOS and its variants Discrete Symbiotic Organisms Search (DSOS) algorithm have been used to solve different optimisation problems including tasks scheduling in cloud computing environment where results obtained are promising in comparison with stateof- the-art metaheuristic algorithms. …”
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Evolutionary low frequency steering vibration control towards human spine
Published 2014“…PSO falls under the umbrella of evolutionary algorithms which is used to optimise and tune the PID controller parameters (Kp, Ki and Kd) based on a predefined performance index. …”
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Proceeding Paper -
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Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat
Published 2024“…This is due to the data generated from the numerical model possess the pattern for the ML algorithm ease of prediction. In addition, Coati Optimization algorithm, Particle Swarm Opimisation (PSO) and Bayesian Optimsiation (BO) are integrated to identify optimal parameters and minimize settlement during twin tunnel excavation and GBT with the optimisation algorithm has shown consistent capability identifying the least SS induced by twin tunnels Keyword: …”
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Aeronautical revenues optimisation model (AROM) for regional airports via airside operations stochastic baseline matrix analysis / Wan Mazlina Wan Mohamed
Published 2016“…The influential variables were determined through literature reviews and case studies of regional airports in the Netherlands and Malaysia, and were validated with regression analysis. Preliminary model was developed based on the determinants and the model was analysed using Bayesian Network theory. …”
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Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm
Published 2018“…Optimisation is difficult to optimise as there are three parameters that need to be tuned, Kp, Integral parameter, Ki, and derivative parameter, Kd. …”
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Monograph -
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…Many optimisation-based intrusion detection algorithms have been developed and are widely used for intrusion identification. …”
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Prediction of Rainfall Trends using Mahalanobis-Taguchi System
Published 2025“…Finally, the validation with T mean-based error (Tmbe) using Mean Absolute Error (MAE) revealed a pattern of errors to provide insight to find the significant parameters of MTS. ? …”
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Mixed-variable ant colony optimisation algorithm for feature subset selection and tuning support vector machine parameter
Published 2017“…This paper presents a hybrid classification algorithm, ACOMV-SVM which is based on ant colony and support vector machine.A new direction for ant colony optimisation is to optimise mixed (discrete and continuous) variables.The optimised variables are then feed into selecting feature subset and tuning its parameters are two main problems of SVM.Most approaches related to tuning support vector machine parameters will discretise the continuous value of the parameters which will give a negative effect on the performance. …”
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Mathematical modelling and hybrid ACO-PSO technique for PV performance improvement
Published 2016“…Secondly, a hybrid Ant Colony Optimisation-Particle Swarm Optimisation (ACO-PSO) algorithm was proposed to optimally determine the MPPT parameters. …”
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Energy and cost integration model for multi-objective optimisation in turning process of stainless steel 316
Published 2019“…A three-confirmation method was used to validate the optimum point. Moreover, the second-generation results of optimization using NSGA II showed an improvement of more than 70% compared with that of RSM optimization. …”
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Single-Solution Simulated Kalman Filter Algorithm for Global Optimisation Problems
Published 2016“…In comparison, the proposed ssSKF algorithm supersedes the original population-based Simulated Kalman Filter (SKF) algorithm by operating with only a single agent, and having less parameters to be tuned. …”
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