Search Results - (( (parameter OR parameters) simulation model algorithm ) OR ( using function method algorithm ))
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1
Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor
Published 2017“…This research focuses on the parameter estimation, outlier detection and imputation of missing values in a linear functional relationship model (LFRM). …”
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2
Predictive modelling of machining parameters of S45C mild steel
Published 2016“…The artificial neural network type Network Fitting Tool (NFTOOL) is used as a modeling technique for manipulating the ideal algorithm parameters. …”
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3
Parameter-driven count time series models / Nawwal Ahmad Bukhari
Published 2018“…Simulation shows that MCEM algorithm and particle method are useful for the parameter estimation of the Poisson model. …”
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4
Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. …”
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Characterization of PV panel and global optimization of its model parameters using genetic algorithm
Published 2023“…The Manufacturer's Data Sheet information is used as a basis for the purpose of parameter optimization, with an average absolute error fitness function formulated; and a numerical iterative method used to solve the voltage-current relation of the PV module. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…We classify the cluster group that exceeds the stopping rule as potential outliers. Model verification of all method and model proposed in this study are examined using the simulation study. …”
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7
Characterization of PV panel and global optimization of its model parameters using genetic algorithm
Published 2013“…The Manufacturer's Data Sheet information is used as a basis for the purpose of parameter optimization, with an average absolute error fitness function formulated; and a numerical iterative method used to solve the voltage-current relation of the PV module. …”
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8
Identification of hammerstain model using stochastic perturbation simultaneous approximation
Published 2016“…Furthermore, the Identification is done using MATLAB Simulink to simulate the Hammerstein Model. …”
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Undergraduates Project Papers -
9
PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM
Published 2011“…To overcome these limitations, there have been attempts to use genetic algorithm (GA) to optimize some of these parameters. …”
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10
Load dispatch optimization of open cycle industrial gas turbine plant incorporating operational, maintenance and environmental parameters
Published 2006“…Simulation results successfully demonstrated that multi-objectives total production cost (TPC) objective functions, the proposed EOH constraint, emissions model and constraints algorithm could be incorporated into the EPL-PSO method which provided optimum results, without violating any of the constraints as defined. …”
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11
Combining Recursive Least Square and Principal Component Analysis for Assisted History Matching
Published 2014“…Next, using simulated data together with historical data, objective function will be computed. …”
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Final Year Project -
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Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques
Published 2003“…In this method of analysis the exponential signal is converted to a convolution model whose input is a train of weighted delta function that contains the signal parameters to be determined.The resolution of the estimated decay rates is poor if the conventional fast Fourier transform (FFT) algorithm is used to analyse the resulting deconvolved data. …”
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Neural Network Model and Finite Element Simulation of Spring back in Plane-Strain Metallic Beam Bending
Published 2006“…Two metamodeling techniques namely the neural network and the response surface methodology are used and compared to approximate two multidimensional functions. …”
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14
Real time nonlinear filtered-x lms algorithm for active noise control
Published 2012“…The NLFXLMS algorithm is a stochastic gradient algorithm that incorporates the derivative of a nonlinear plant model which is represented by the scaled error function (SEF) in the controller design. …”
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15
Novel farmland fertility algorithm based PIDPSS design for SMIB angular stability enhancement
Published 2020“…For this study, design of proportional integral derivative (PID) PSS (PIDPSS) is proposed for damping oscillations and improve angular stability in single machine infinite bus (SMIB) power system modeled and simulated in MATLAB/SIMULINK. A new metaheuristics method called Farmland Fertility Algorithm (FFA) inspired by nature is proposed for optimal design of PIDPSS using a robust ISTSE objective function which had to be minimized. …”
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The effect of adaptive parameters on the performance of back propagation
Published 2012“…The Back Propagation algorithm or its variation on Multilayered Feedforward Networks is widely used in many applications. …”
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17
Location determination using radio frequency RSSI and deterministic algorithm
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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19
Modeling the powder compaction process using the finite element method and inverse optimization
Published 2011“…This paper focuses on studying and adapting modeling techniques using the finite element method to simulate the rigid die compaction of metal powders. …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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