Search Results - (( parameter simulation based algorithm ) OR ( _ continuous function algorithm ))
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1
Identification of hammerstain model using stochastic perturbation simultaneous approximation
Published 2016“…Besides that, this project analysed the efficient of the SPSA in identify nonlinear system in term of object function and error with different noise variance. A numerical example is given to illustrate that the SPSA based algorithms can give accurate parameter estimate of the Hammerstein models with high probability through detailed simulation.…”
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Undergraduates Project Papers -
2
Mathematical modelling of mass transfer in a multi-stage rotating disc contactor column
Published 2005“…This derivation initiated the formulation of the modified quadratic driving force, called Time-dependent Quadratic Driving Force (TQDF). Based on this formulation, a Mass Transfer of A Single Drop (MTASD) Algorithm was designed, followed by a more realistic Mass Transfer of Multiple Drops (MTMD) Algorithm which was later refined to become another algorithm named the Mass Transfer Steady State (MTSS) Algorithm. …”
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3
A graphical user interface application for continuous-time identification of dynamical system
Published 2002“…The GUI based on MATLAB consists of data preprocessing, parameter estimation, model validation and model simulation. …”
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Article -
4
Switching algorithm to avoid attitude representation singularity
Published 2009“…In this paper, the singularity associated with a minimal attitude parameterization using Euler angles is avoided by a switching algorithm. This algorithm is based on describing the attitude as a function of time with two sets of Euler angle sequences that possess nonconjunctive singularities. …”
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Proceeding Paper -
5
Hybridization of nonlinear sine cosine and safe experimentation dynamics algorithms for solving control engineering optimization problems
Published 2024“…In response to this imperative, researchers have increasingly turned to optimization-based approaches, with the Sine Cosine Algorithm (SCA) emerging as a prominent solution. …”
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6
Integrated geophysical, hydrogeochemical and artificial intelligence techniques for groundwater study in the Langat Basin, Malaysia / Mahmoud Khaki
Published 2014“…These results confirm that, for all the networks the Levenberg-Marquardt algorithm is the most effective algorithm to model the groundwater level. …”
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7
Switching principles to circumvent Euler angle singularity
Published 2010“…The algorithm is numerically demonstrated and validated by a nonlinear six degree of freedom closed-loop spacecraft simulation test.…”
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Proceeding Paper -
8
Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller
Published 2010“…It is observed that the APFLC showed convincing performance over the entire simulation of the Pico-satellite. Genetic Algorithm (GA) is a computational model inspired by evaluation. …”
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9
Modeling And Optimization Of Lipase-Catalyzed Synthesis Of Adipate Esters Using Response Surface Methodology And Artificial Neural Network
Published 2010“…Various feedforward neural networks were performed using different learning algorithms. The best algorithm was found to be Levenberg–Marquardt (LM) for a network composed of seven hidden nodes with hyperbolic tangent sigmoid transfer function. …”
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10
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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11
Fuzzy-based multi-agent approach for reliability assessment and improvement of power system protection
Published 2015“…In addition, another two agents have been developed based on Monte Carlo simulation. The first agent employed fuzzy parameters such as, current with its means and variances and the second agent is the probability of outage capacity for each state. …”
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12
Optimization of turning parameters using genetic algorithm method
Published 2008“…The simulation based on Genetic Algorithm are successful develop and the optimum parameters values are obtained from the simulation.…”
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Undergraduates Project Papers -
13
PSAT : a pairwise test data generation tool based on simulated annealing algorithm
Published 2015“…This research is about the research on developing a Pairwise Test Data Generation Tool based on Simulated Annealing (SA) algorithm which named as PSAT. …”
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Undergraduates Project Papers -
14
Vehicular traffic noise prediction and propagation modelling using artificial neural network
Published 2018“…The optimal radial basis function NN model was used which comprised of 17 hidden layers with a back-propagation algorithm. …”
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15
Optimization of milling parameters using ant colony optimization
Published 2008“…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
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Undergraduates Project Papers -
16
The Implementation of a Machine Learning-based Routing Algorithm in a Lab-Scale Testbed
Published 2024Subjects:Conference Paper -
17
Hybrid Predictive- Neural Network Based On Proton Exchange Membrane Fuel Cell Maximum Power Point Tracking
Published 2023“…This project's objective is to simulate a fully functional PEMFC system that is based on mathematical models and combines them with an artificial neural network. …”
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Final Year Project Report / IMRAD -
18
Parameter-Less Simulated Kalman Filter
Published 2017“…Simulated Kalman Filter (SKF) algorithm is a new population-based metaheuristic optimization algorithm. …”
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19
GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE
Published 2020“…The behavior of Genetic Algorithm (GA) where it generates and evolves the parameters towards a high-quality solution gives an advantage in obtaining ideal combination of parameters to fit in with the simulation. …”
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Final Year Project -
20
Modeling of Functional Electrical Stimulation (FES): Powered Knee Orthosis (PKO) assisted gait exercise in post-stroke rehabilitation / Adi Izhar Che Ani
Published 2023“…In the human gait model, three Machine Learning algorithms were used: Gaussian Process Regression, Support Vector Machine, and Decision Tree. …”
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Thesis
