Search Results - (( based regression methods algorithm ) OR ( parameter estimation using algorithm ))

Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

“…The multi-class classification strategy is used to ensure quick estimation of the multi-class NN algorithms. …”
Get full text
Get full text

Dynamic robust bootstrap method based on LTS estimators by Midi, Habshah, Uraibi, Hassan Sami, Al-Talib, Bashar Abdul Aziz Majeed

“…We call this method Dynamic Robust Bootstrap-LTS based (DRBLTS) because here we have employed the LTS estimator in the modified bootstrap algorithm. …”
Get full text
Get full text

Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

“…Lastly, we consider the problem of detecting multiple outliers in circular regression models based on the clustering algorithm. …”
Get full text
Get full text

Model selection approaches of water quality index data by Kamarudin, Nur Azulia, Ismail, Suzilah

“…In order to select the best model, it is vital to ensure that proper estimation method is chosen in the modelling process.Different estimators have been proposed for the estimation of parameters of a model, including the least square and iterative estimators.This study aims to evaluate the forecasting performances of two algorithms on water quality index (WQI) of a river in Malaysia based on root mean square error (RMSE) and geometric root mean square error (GRMSE).Feasible generalised least squares (FGLS) and iterative maximum likelihood (ML) estimation methods are used in the algorithms, respectively.The results showed that SUREMLE-Autometrics has surpassed SURE-Autometrics; another simultaneous selection procedure of multipleequation models.Two individual selections, namely Autometrics-SUREMLE and Autometrics-SURE, though showed consistency only for GRMSE.All in all, ML estimation is a more appropriate method to be employed in this seemingly unrelated regression equations (SURE) model selection.…”
Get full text
Get full text
Get full text

Bayesian survival and hazard estimates for Weibull regression with censored data using modified Jeffreys prior by Ahmed, Al Omari Mohammed

“…Next we consider both the scale and shape parameters to be unknown under censored data. It is observed that the estimate of the shape parameter under the maximum likelihood method cannot be obtained in closed form, but can be solved by the application of numerical methods. …”
Get full text
Get full text

Parameter estimation of stochastic differential equation by Haliza Abd. Rahman, Arifah Bahar, Norhayati Rosli, Madihah Md. Salleh

“…Spline approach consists of regression spline and smoothing spline. Regression spline with Bayesian approach is considered in the first step of a two-step method in estimating the structural parameters for stochastic differential equation (SDE). …”
Get full text
Get full text
Get full text

Scene illumination classification based on histogram quartering of CIE-Y component by Hesamian, Mohammad Hesam

“…Those algorithms which performed estimation carrying out lots of calculation that leads in expensive methods in terms of computing resources. …”
Get full text
Get full text

Outlier Detections and Robust Estimation Methods for Nonlinear Regression Model Having Autocorrelated and Heteroscedastic Errors by Riazoshams, Hossein

“…The ordinary Nonlinear Least Squares (NLLS) and the Maximum Likelihood Estimator (MLE) techniques are often used to estimate the parameters of nonlinear models. …”
Get full text
Get full text

Bayesian logistic regression model on risk factors of type 2 diabetes mellitus by Chiaka, Emenyonu Sandra

“…Estimates of the coefficients for the variables are obtained via the method of maximum likelihood based on the frequentist point of view. …”
Get full text
Get full text

Restoration of blurred images using geometric and chebichef moments / Ahlad Kumar by Ahlad, Kumar

“…Once the blur parameters are estimated, image restoration of the proposed method is carried out using split Bregman algorithm. …”
Get full text
Get full text

Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin by Mohd Yassin, Ahmad Ihsan

“…The identification process of NARX/NARMA/NARMAX involves structure selection and parameter estimation, which can be simultaneously performed using the widely accepted Orthogonal Least Squares (OLS) algorithm. …”
Get full text
Get full text

Robust techniques for linear regression with multicollinearity and outliers by Mohammed, Mohammed Abdulhussein

“…Hence, we propose a new estimation method namely the modified GM-estimator (MGM) based on MGDFF. …”
Get full text
Get full text

Modified least trimmed squares method for face recognition / Nur Azimah Abdul Rahim by Abdul Rahim, Nur Azimah

“…The genetic algorithm configuration for n (number of observations) and p (parameter) was changed to assess the performance of modified method. …”
Get full text
Get full text

A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…Firefly algorithm outperformed the other metaheuristic algorithms used to solve this proposed hybrid artificial intelligence model regarding parameter sensitivity. …”
Get full text
Get full text
Get full text

Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model by Elfaki, Faiz. A. M.

“…From the simulation study for this particular case, we can conclude that the EM algorithm proved to be more superior in terms of mean value of parameter estimates, bias and root mean square error. …”
Get full text
Get full text

Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

“…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. …”
Get full text
Get full text
Get full text
Get full text

Comparison of Conjugate Gradient methods for developing the multiple linear regression model for rubber yield in Malaysia / Anis Shahida Rohimi Ozeman by Rohimi Ozeman, Anis Shahida

Get full text
Get full text

Robust Estimation Methods And Outlier Detection In Mediation Models by Fitrianto, Anwar

“…Simple mediation model consists of three regression equations. The Ordinary Least Squares (OLS) method is often use to estimate the parameters of the mediation model. …”
Get full text
Get full text

Proving the efficiency of alternative linear regression model based on mean square error (MSE) and average width using aquaculture data by Awang Nawi, Mohamad Arif, Wan Ahmad, Wan Muhamad Amir, Mohd Ibrahim, Mohamad Shafiq, Mamat, Mustafa, Khamis, Mohd Fahdli, Mohamed, Mohamad Afendee

“…The results of the study showed a positive improvement for the estimation of parameters generated through these alternative methods. © BEIESP.…”
Get full text
Get full text
Get full text
Get full text

Development of a hybrid PSO-ANN model for estimating glucose and xylose yields for microwave-assisted pretreatment and the enzymatic hydrolysis of lignocellulosic biomass by Mohammad, Saleem Ethaib, Omar, Rozita, Mustapa Kamal, Siti Mazlina, Awang Biak, Dayang Radiah, S., Syafiie

“…ANN is a powerful tool capable of determining the relationship between the desired input and output data while PSO was used as a robust population-based search algorithm to optimize the performance of the ANN model. …”
Get full text
Get full text
Get full text