Search Results - (( based classification method algorithm ) OR ( parameter estimation modified algorithm ))
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1
Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network
Published 2017“…MVPA-CNN based proposed algorithm is compared with region of interest (ROI) based method and MVPA based estimated values. …”
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Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
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Thesis -
3
Robust techniques for linear regression with multicollinearity and outliers
Published 2016“…Hence, we propose a new estimation method namely the modified GM-estimator (MGM) based on MGDFF. …”
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4
Parameter estimation of tapioca starch hydrolysis process: application of least squares and genetic algorithm
Published 2005“…The performance of genetic algorithm (GA) in nonlinear kinetic parameter estimation of topiaca starch hydrolysis was studied and compared with Gauss-Newton method. …”
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Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane
Published 2021“…The efficiency of the proposed HMVOSCA algorithm is evaluated using the convergence curve, parameter estimation error, bode plot, function plot, and Wilcoxon's test method. …”
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Conference or Workshop Item -
7
Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data
Published 2023“…However, the selection of the most suitable estimators is still a challenging task. The present study proposes a simulated annealing algorithm (SA) in estimating the parameters of Weibull distribution with application to modified internal rate of return data (MIRR).The objective is to examine the investment potential of the shari’ah compliance companies of the Malaysia property sector (MPS). …”
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8
A simple and fast algorithm to estimate effective anisotropy parameters
Published 2014“…To resolve above issues, we implement the modified and extended Backus's averaging algorithm to estimate the effective stiffness parameters and anisotropic parameters, which is very consistent with the well logs and successfully distinguished potential reservoir embedded by shale.…”
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Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems
Published 2011“…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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10
Power System State Estimation In Large-Scale Networks
Published 2010“…The developed program is suitable either to estimate the UPFC controller parameters or to estimate these parameter values in order to achieve the given control specifications in addition to the power system state variables.…”
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11
Analysis of multicomponent transient signals using music superresolution technique
Published 2008“…It is shown that with this technique parameter estimates do not significantly change with Signal to Noise Ratio. …”
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Proceeding Paper -
12
LASSO-type estimations for threshold autoregressive and heteroscedastic time series models.
Published 2020“…In this thesis, we propose Least Absolute Shrinkage and Selection Operator (LASSO) type estimators to perform simultaneous parameter estimation and model selection for five specific univariate and multivariate time series models, and develop several algorithms to compute these estimators. …”
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UMK Etheses -
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Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques
Published 2003“…Parameter estimation of transient signals, having real decaying exponential constants, is a difficult but important problem that often arises in many areas of scientific disciplines. …”
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Simultaneous computation of model order and parameter estimation for ARX model based on single swarm and multi swarm simulated Kalman filter
Published 2017“…Simultaneous Model Order and Parameter Estimation (SMOPE) and Simultaneous Model Order and Parameter Estimation based on Multi Swarm (SMOPE-MS) are two techniques of implementing meta-heuristic algorithm to iteratively establish an optimal model order and parameters simultaneously for an unknown system. …”
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Case Slicing Technique for Feature Selection
Published 2004“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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Thesis -
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ADAPTIVE LINEAR ALGORITHMS FOR POWER SYSTEM FUNDAMENTAL AND HARMONIC ESTIMATION
Published 2015“…Hence, one of the objectives of this thesis is to address and enhance the introduced fundamental frequency adaptive filter method which was based on modified variable step size LMS (MVSS) algorithm using generalized square error normalized LMS algorithm. …”
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17
Knowledge base processing method based on text classification algorithm
Published 2023“…The text classification algorithm's knowledge base processing method utilizes existing data from the knowledge base to guide the construction and training of the classification model. …”
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Conference or Workshop Item -
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Optimal parameter estimation of MISO system based on fuzzy numbers / Razidah Ismail ... [et al.]
Published 2006“…Thus, this paper discusses the development of a Fuzzy State Space algorithm for optimal parameter estimation in multiple-input single-output (MISO) system based on fuzzy numbers. …”
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19
Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach
Published 2009“…The method was developed based on the grid structure, whereby it was done to create a successful method of improving performance in classification. …”
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Thesis -
20
Grid base classifier in comparison to nonparametric methods in multiclass classification
Published 2010“…The method was developed based on the grid structure which was done to create a powerful method for classification. …”
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