Search Results - (( parameter optimisation based algorithm ) OR ( parameter evaluation system algorithm ))
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A comparative evaluation of PID-based optimisation controller algorithms for DC motor
Published 2023“…Controllers; DC motors; Electric control equipment; Particle swarm optimization (PSO); Proportional control systems; Three term control systems; Two term control systems; Backtracking search algorithms; Comparative analysis; Comparative evaluations; Controller algorithm; Industrial activities; Optimum parameters; Particle swarm optimisation; Proportional integral derivative controllers; Electric machine control…”
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Performance Comparison of Particle Swarm Optimization and Gravitational Search Algorithm to the Designed of Controller for Nonlinear System
Published 2014“…This paper presents backstepping controller design for tracking purpose of nonlinear system. Since the performance of the designed controller depends on the value of control parameters, gravitational search algorithm (GSA) and particle swarm optimization(PSO) techniques are used to optimise these parameters in order to achieve a predefined system performance. …”
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Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates
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PID-based control of a single-link flexible manipulator in vertical motion with genetic optimisation
Published 2009“…The important point is to evaluate the range of PID parameter which used in the GAs programmed to find the best value of this parameter. …”
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Proceeding Paper -
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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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Thesis -
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Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification
Published 2023“…The performance of FESSIC was evaluated against ten benchmark image classification algorithms and six classifiers on four ground-based sky image datasets. …”
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A Study of the Contribution of Nearest-Neighbour Thermodynamic Parameters to the DNA Sequences Generated by Ant Colony Optimisation
Published 2013“…The Watson-Crick base pair ∆Go37 was used as the distance between nodes for the thermodynamic parameters in the problem models for the heuristic approach in the ACS algorithms. …”
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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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Modelling and calibration of high-pressure direct injection compressed natural gas engine
Published 2021“…The objectives of the study are 1) to analyse the effect of HPDI-CNG system configuration and influential parameters, 2) to evaluate the injector mass flow rate and its suitability to fulfil engine requirement, 3) to assess the HPDI-CNG vehicle performance as a whole, and 4) to calibrate the electronic control unit (ECU) base maps by using MBC procedure. …”
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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
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Seamless vertical handover technique for vehicular ad-hoc networks using artificial bee colony-particle swarm optimisation
Published 2019“…Firstly, we proposed a multi-criteria artificial bee colony hybrid with particle swarm optimisation algorithm (MC ABC-PSO) for evaluating the information gathered from the mobile nodes in the handover. …”
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Evaluating Adan vs. Adam: an analysis of optimizer performance in deep learning
Published 2025“…On the other hand, for image classification tasks, Adan provides more consistent optimisation across extended training periods. Based on these results, this paper aims to provide insights into the strengths and limitations of each optimizer, highlighting the importance of considering task-specific requirements when selecting an optimization algorithm for deep learning models.…”
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Proceeding Paper -
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New techniques incorporating computational intelligence based for voltage stability evaluation and improvement in power system / Nur Fadilah Ab. Aziz
Published 2014“…Therefore, this thesis presents novel techniques for voltage stability evaluation and enhancement in power system. Firstly, a new bus voltage stability index named as Voltage Stability Condition Indicator (VSCI) was developed. …”
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Optimal PI controller based PSO optimization for PV inverter using SPWM techniques
Published 2023Article -
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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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Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination
Published 2025“…In this context. ML algorithms provide powerful data driven means to model complex relationship within experimental datasets to improve process optimisation This study systematically evaluated several supervised ML models, including Random Forest (RF) Support Vector Machines (SVM), Ridge Regression, Lasso Regression, Decision Tree, Extra Tree Regression, Gradient Boost, and XGBoost, to predict removal efficiency in GHBD system. …”
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Hardware-in-the-loop study of a hybrid active force control scheme of an upper-limb exoskeleton for passive stroke rehabilitation
Published 2018“…A data-driven model is developed based on the exoskeleton prototype built. A hardware-in-the-loop simulation is carried out to evaluate the appropriate gains of both the PD and the AFC inertial parameter gained that is tuned via the SKF algorithm. …”
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Hardware-in-the-loop study of a hybrid active force control scheme of an upper-limb exoskeleton for passive stroke rehabilitation
Published 2018“…A data-driven model is developed based on the exoskeleton prototype built. A hardware-in-the-loop simulation is carried out to evaluate the appropriate gains of both the PD and the AFC inertial parameter gained that is tuned via the SKF algorithm. …”
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Thesis -
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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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