Search Results - (( _ optimisation model algorithm ) OR ( parameter optimization method algorithm ))
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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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Augmented model based double iterative loop techniques for integrated system optimisation and parameter estimation of large scale industrial processes
Published 1993“…The methods incorporate integrated system optimisation and parameter estimation which utilizes process measurements to achieve real process optimality inspite of model reality differences. …”
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The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm
Published 2020“…The proposed algorithm has been compared with the other three famous algorithms, which are Particle Swarm Optimization (PSO), Differential Evolutionary (DE), and Bees Optimization Algorithm (BOA). …”
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The potential of a novel support vector machine trained with modified mayfly optimization algorithm for streamflow prediction
Published 2023“…Balancing; Forecasting; Stream flow; Support vector machines; Exploitation and explorations; Machine learning models; Optimisations; Optimization algorithms; Prediction modelling; Simulated annealing integrated with mayfly optimization; Streamflow prediction; Support vector regression models; Support vector regressions; Support vectors machine; Simulated annealing; algorithm; mayfly; optimization; prediction; streamflow; support vector machine; Jhelum River…”
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Application of a primal-dual interior point algorithm using exact second order information with a novel non-monotone line search method to generally constrained minimax optimizatio...
Published 2008“…This work presents the application of a primal-dual interior point method to minimax optimisation problems. The algorithm differs significantly from previous approaches as it involves a novel non-monotone line search procedure, which is based on the use of standard penalty methods as the merit function used for line search. …”
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Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system
Published 2010“…The particle swarm optimization (PSO) method is used to tune the parameters of the controller and weighting functions subject to QFT and/or constraints. …”
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Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models
Published 2024“…This study proposes ensemble models for predicting LDC based on multilayer perceptron (MULP) methods and optimization algorithms. The honey badger optimization algorithm (HBOA), salp swarm algorithm (SASA), firefly algorithm (FIFA), and particle swarm optimization algorithm (PASOA) are used to adjust the MULP parameters. …”
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Investigation of Meta-heuristics Algorithms in ANN Streamflow Forecasting
Published 2024Subjects:Article -
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Harmony Search Approach In The Strut And Tie Model To Optimise The Stress Distribution In A Concrete Box Girder
Published 2021“…This study aims to develop a stress optimisation model using harmony search (HS) algorithm to control and limit cracks in the concrete. …”
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Final Year Project / Dissertation / Thesis -
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Multi-objectives process optimization in end milling process of aluminium alloy 6061-T6 using genetic algorithm
Published 2024“…For future study, other methods or algorithms can be applied in other machining processes to obtain optimum machining parameters.…”
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Conference or Workshop Item -
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PID-based control of a single-link flexible manipulator in vertical motion with genetic optimisation
Published 2009“…The dynamic model of the system is derived using the Lagrange equation and discretised using the finite difference (FD) method. GA optimization is used to optimize the parameters of the proportional-integral-derivative (PID) based controllers for control of rigid-body and flexible motion dynamics of the system. …”
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Proceeding Paper -
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Application of response surface methodology coupled with genetic algorithm in the optimization of cutting conditions for surface roughness in end-milling of Inconel 718 using coate...
Published 2007“…This paper presents an efficient method of optimisation of surface roughness in end milling of Inconel 718 using TiAlN coated inserts under dry conditions by coupling response surface methodology (RSM) with genetic algorithm (GA). …”
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Proceeding Paper -
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Multi objective optimisation for high speed end milling using simulated annealing algorithm
Published 2015“…This paper presents the optimization of machining parameters in end milling processes by using the simulated annealing algorithm (SAA) as one of the unconventional methods in optimization. …”
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An optimization method of genetic algorithm for lssvm in medium term electricity price forecasting
Published 2023“…This is due to the limited historical data for training and testing purposes. Therefore, an optimisation technique of Genetic Algorithm (GA) for Least Square Support Vector Machine (LSSVM) was developed in this study to provide an accurate electricity price forecast with optimised LSSVM parameters and input features. …”
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Energy and cost integration model for multi-objective optimisation in turning process of stainless steel 316
Published 2019“…Analysis of variance and the regression model was used to analyze the machining parameters and responses. A multi-objective optimization method was employed to optimize machining parameters in terms of energy and cost models. …”
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Analytical Modelling And Efficiency Optimisation Of Permanent Magnet Synchronous Machine Using Particle Swarm Optimisation
Published 2018“…Subsequently, an intelligent computational algorithm - Particle Swarm Optimization (PSO) was later applied to all the machine variables simultaneously to find the optimal solution for a compromised optimal machine performance. …”
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Optimisation of support vector machine hyperparameters using enhanced artificial bee colony variant to diagnose breast cancer
Published 2023“…The performance of SVM can be affected by hyperparameters, which are kernel scale and known as gamma and regularization parameters (C). A metaheuristic algorithm is introduced to optimise the hyperparameters. …”
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