Search Results - (( using simulation model algorithm ) OR ( parameter optimisation based algorithm ))
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1
Augmented model based double iterative loop techniques for integrated system optimisation and parameter estimation of large scale industrial processes
Published 1993“…The double iterative loop structures of the proposed algorithms use the real process measurement within the outer loops while the inner loops involve model based computation only. …”
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Modelling and optimisation of blood glucose control for type 1 diabetes using multi-parametric programming and model-based predictive control (mp-MPC) / Associate Professor Dr Ayub...
Published 2014“…AU simulation and optimisation works are carried out using gPROMS™. …”
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Monograph -
3
Optimisation of laser cutting parameters of oil palm wood / Harizam Mohd Zin
Published 2013“…In some cases, the prediction errors of Taguchi ANN model was found larger than 10% even using a Levenberg Marquardt training algorithm. …”
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4
Optimisation of fed-batch fermentation process using deep reinforcement learning
Published 2023“…The kinetic and dynamic behaviour of the fed-batch baker’s yeast fermentation was simulated and modelled using MATLAB, with no experimental work carried out. …”
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5
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. …”
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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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7
Sensorless Adaptive Fuzzy Logic Control Of Permanent Magnet Synchronous Motor
Published 2008“…The design and optimisation of the FLC are carried out using an adaptive fuzzy inference system network that uses the backpropagation, least square and gradient algorithms. …”
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8
Ocean Colour Remote Sensing Of Case 2 Waters Using An Optimised Neural Network
Published 2016“…The NN model architecture and training parameters were optimised, with inputs being selected based correlation analysis (CA) and principal component analysis (PCA). …”
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9
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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Modelling and calibration of high-pressure direct injection compressed natural gas engine
Published 2021“…The MBC procedure was carried out by using the MBC Toolbox of Matlab. The calibration framework consists of the development of the data-driven model by using ANN and ECU parameters optimisation by using GA. …”
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11
Control of an underactuated double-pendulum overhead crane using improved model reference command shaping: Design, simulation and experiment
Published 2024journal::journal article -
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A new history matching sensitivity analysis framework with random forests and Plackett-Burman design
Published 2017“…Once the samples are ready, the parameters' input values and the target vector (i.e. the history matching error vector) are used to construct a Random Forests model. This model is used to rank the importance of each history matching parameter. …”
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Design and development of fanger model and fuzzy logic based controller for air conditioners
Published 2019“…To validate the performance of the proposed model, the results from both microcontroller prototype and MATLAB simulation are compared for validation purpose. …”
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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. …”
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15
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 -
16
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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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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Modelling and Control of Ankle Foot Orthosis (AFO) for Children Utilising Soft Computing Towards Intelligent Approach
Published 2024“…The PID controllers were tuned automatically by the PSO algorithm based on the same identified models. The performance of both developed controllers was compared and analyzed. …”
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Optimal PI controller based PSO optimization for PV inverter using SPWM techniques
Published 2023Article -
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