Search Results - (( normal distribution function algorithm ) OR ( parameter simulation study algorithm ))
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1
Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…For its fast convergence and for its efficient search procedure, the self-adaptation is proposed in the parameters of the proposed hybrid algorithm. The effectiveness of this algorithm is verified by applying it on the unconstrained and constrained test functions through a simulation study. …”
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2
Modeling The Modified Internal Rate Of Return (Mirr) For Long-Term Investment Strategy By The Assumption Of Gamma Distribution
Published 2023“…Alternative approaches such as the Simulated Annealing (SA) algorithm, which maximizes the log-likelihood function, and Bayesian MCMC estimation are considered. …”
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3
PSO modelling and PID controlled of automatic fish feeder system
Published 2020“…In this study, raw data at distribution part with speed of 130 rpm, 160 rpm, 190 rpm, 220 rpm and 250 rpm were extracted and used to determine ARX equation parameters as transfer function by using PSO algorithm to optimize ARX model parameter. …”
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4
Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…The NPO is inspired by the lifestyle of the nomads. The proposed algorithm simulates the behavior of the nomads when they are searching for life sources (water or grazing fields). …”
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5
Reservoir Inflow Forecasting Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System Techniques
Published 2007“…The model was trained based on the Leven-berg Marquardt algorithm with sigmoid activation functions. Simulation results for the independent testing data series showed that the model can perform well in simulating peak flows as well as base flows. …”
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6
Determining penetration limit of central distributed generation topology in radial distribution networks
Published 2021“…Therefore, the study proposed a comparison between the conventional bus dedicated distributed generation topology and the central distributed generation topology. …”
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7
Parameter-Less Simulated Kalman Filter
Published 2017“…Further studies on the effect of P(0), Q and R values suggest that the SKF algorithm can be realized as a parameter-less algorithm. …”
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8
Optimal network reconfiguration and intelligent service restoration prediction technique based on Cuckoo search spring algorithm / Mohamad Izwan Zainal
Published 2022“…In addition, objective function using the same CSSA algorithm were applied i.e., Vmin and Ploss as the objective function, and multi-objective involves Vmin and Ploss as the objective function. …”
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9
Optimization of turning parameters using genetic algorithm method
Published 2008“…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
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Undergraduates Project Papers -
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
Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor
Published 2017“…This study begins by proposing a robust technique for estimating the slope parameter in LFRM. …”
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12
Estimation in spot welding parameters using genetic algorithm
Published 2007“…In this study, parameter of spot welding estimate using computer simulation. …”
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13
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 -
14
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 -
15
The Implementation of a Machine Learning-based Routing Algorithm in a Lab-Scale Testbed
Published 2024“…Thus, researchers are developing intelligent RAs, including machine learning (ML)-based algorithms to meet traffic Q oS r equirements. However, most current studies evaluate performance using simulations. …”
Conference Paper -
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Robust Kernel Density Function Estimation
Published 2010“…To do this evaluation, the mixtures of bivariate normal distribution with different percentage of contribution are simulated. …”
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17
Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…This study proposed an improved parameter estimation procedure for PEMFCs by using the GOOSE algorithm, which was inspired by the adaptive behaviours found in geese during their relaxing and foraging times. …”
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18
Profit-based optimal generation scheduling of a microgrid
Published 2023“…grid). Current methods normally assume either islanded operation, or utilitygrid connected ?…”
Conference paper -
19
Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah
Published 2015“…Empirical cumulative distribution function (CDF) model is presented in evaluating the real traffic distribution. …”
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A simulation study of a parametric mixture model of three different distributions to analyze heterogeneous survival data
Published 2013“…In this paper a simulation study of a parametric mixture model of three different distributions is considered to model heterogeneous survival data.Some properties of the proposed parametric mixture of Exponential, Gamma and Weibull are investigated.The Expectation Maximization Algorithm (EM) is implemented to estimate the maximum likelihood estimators of three different postulated parametric mixture model parameters.The simulations are performed by simulating data sampled from a population of three component parametric mixture of three different distributions, and the simulations are repeated 10, 30, 50, 100 and 500 times to investigate the consistency and stability of the EM scheme.The EM Algorithm scheme developed is able to estimate the parameters of the mixture which are very close to the parameters of the postulated model.The repetitions of the simulation give parameters closer and closer to the postulated models, as the number of repetitions increases, with relatively small standard errors.…”
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