Search Results - (( parameter simulation study algorithm ) OR ( parameter optimisation based algorithm ))
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A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application
Published 2011“…The optimal simulation parameters can be used for the real application. …”
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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“…Three simulation works are carried out using three different algorithms so as to refine the performance of the controller. …”
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Monograph -
3
Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network
Published 2022“…Finally, an AHP was integrated with FA to form Firefly Analytical Hierarchy Algorithm (FAHA) to automatically calculate the weight of each objective function based on the load flow outputs followed by the optimisation process. …”
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4
Dynamic Probability Selection for Flower Pollination Algorithm based on Metropolis-hastings Criteria
Published 2021“…However, FPA still suffers from variability of its performance as there is no one size that fits all values for pa, depending on the characteristics of the optimisation function. This paper proposed flower pollination algorithm metropolis-hastings (FPA-MH) based on the adoption of Metropolis-Hastings criteria adopted from the Simulated Annealing (SA) algorithm to enable dynamic selection of the pa probability. …”
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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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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
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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A new history matching sensitivity analysis framework with random forests and Plackett-Burman design
Published 2017“…The proposed sensitivity analysis framework starts with generating samples/simulations using Plackett- Burman design. Here, each simulation is executed based on different combinations of the parameters' input values. …”
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Modelling and calibration of high-pressure direct injection compressed natural gas engine
Published 2021“…The calibration framework consists of the development of the data-driven model by using ANN and ECU parameters optimisation by using GA. Based on stated methodologies, the following findings were recorded; the analytical model of the HPDI-CNG vehicle predicted a maximum of 123.11 Nm of brake torque at 60 bar of injection pressure. …”
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10
Energy and cost integration model for multi-objective optimisation in turning process of stainless steel 316
Published 2019“…With a simulation in Design Expert and Matlab, the multi-response optimization problems were solved with a response surface methodology (RSM) and non-dominated sorting genetic algorithm (NSGA II), as well as integration between them. …”
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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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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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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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Design and development of fanger model and fuzzy logic based controller for air conditioners
Published 2019“…With the developed algorithm and controller prototype, energy consumption is optimised or minimised for the best financial outcome without sacrifice of human comfort. …”
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Recent Development of Grid-Connected Microgrid Scheduling Controllers for Sustainable Energy: A Bibliometric Analysis and Future Directions
Published 2025“…A substantial total of 63.56% articles were published based on simulation while 18.6%, 13.95% and 3.87% of total articles were published on the experimental setup, critical analysis and review-based study. …”
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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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Single-solution Simulated Kalman Filter algorithm for global optimisation problems
Published 2018“…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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Single-solution Simulated Kalman Filter algorithm for global optimisation problems
Published 2018“…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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