Search Results - (( variable detection method algorithm ) OR ( variable estimation using algorithm ))

Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data by Baba, Ishaq Abdullahi

“…The performance of the proposed method is illustrated using simulation study and on glass vessel data with 1920 variables, cardiomyopathy microarray data with 6319 variables, and octane data with 226 dimensions. …”
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Robust Estimation Methods And Outlier Detection In Mediation Models by Fitrianto, Anwar

“…The Ordinary Least Squares (OLS) method is often use to estimate the parameters of the mediation model. …”
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Coronary artery stenosis detection and visualization / Tang Sze Ling by Tang, Sze Ling

“…In contrast to the conventional methods which perform detection from a single image, the stenosis detection algorithm using two images from various view angles to avoid false positive (stenosis overestimated) and false negative (stenosis underestimated). …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

“…The von Mises distribution is the most commonly used probability distribution of a circular random variable, and the concentration of a circular data set is measured using the mean resultant length. …”
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Robust remote heart rate estimation from multiple asynchronous noisy channels using autoregressive model with Kalman filter by Nooralishahi, Parham, Loo, Chu Kiong, Shiung, Liew Wei

“…We propose a novel algorithm to estimate heart rate. Also, it can differentiate between a photo of a human face and an actual human face meaning that it can detect false signals and skip them. …”
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Power System State Estimation In Large-Scale Networks by NURSYARIZAL MOHD NOR, NURSYARIZAL

“…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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An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction by Ahanin, Fatemeh

“…In the second method, a new traffic estimation method is proposed using Fuzzy C-Mean (FCM) clustering and Minimum Description Length (MDL). …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

“…Due to the inherent and uncertain variability of the Harumanis features, fuzzy learning algorithm has been designed to classify these fruits similar to the ability of human experts. …”
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Estimation of non-contact smartphone video-based vital sign monitoring using filtering and standard color conversion techniques by Qayyum, A., Malik, A.S., Shuaibu, A.N., Nasir, N.

“…This rPPG signal could perform better as compared to the standard vital signs estimation methods. The Inter beat interval (IBI) based on maximum peak detection approach has been used for heart rate variability estimation. …”
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Improved robust estimator and clustering procedures for multivariate outliers detection by Sharifah Sakinah, Syed Abd Mutalib

“…One of the methods to detect outliers in multivariate data is by using distance-based methods, which is Mahalanobis distance (MD). …”
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Speed sensorless control for PMSM drives using Extended Kalman Filter by Mat Lazi, Jurifa, Nordin, Mohamad Ikhwan, Talib, Md Hairul Nizam, Ibrahim, Zulkifilie

“…Therefore, this project proposes sensorless control using an EKF. This method provides an optional estimation algorithm for the non-linear system that can produce a fast and accurate estimation of state variables. …”
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Gene Selection For Cancer Classification Based On Xgboost Classifier by Teo, Voon Chuan

“…XGBoost Classifier is applied in this research, which it is an efficient open-source implementation of the gradient boosted trees algorithm. Gradient boosting is a supervised learning algorithm, which attempts to accurately predict a target variable by combining the estimates of a set of simplifier, weaker models. …”
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Modeling of cupping suction system based on system identification method by Kavindran, Suresh

“…The input and output data were used to create this modeling output variable of the cupping suction system is detected by connecting a differential pressure sensor to the cup, while the input variable is determined by the speed of the pump applied in various locations. …”
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Error concealment technique using wavelet neural network for wireless transmitted digital images by Al-Azzawi, Alaa Khamees

“…Next, a multi-directional interpolation (MDI) technique is proposed. The method is used to estimate the lost coefficients in the wavelet-domain. …”
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Tree species and aboveground biomass estimation using machine learning, hyperspectral and LiDAR data / Nik Ahmad Faris Nik Effendi by Nik Effendi, Nik Ahmad Faris

“…Besides, Artificial Neural Network (ANN) and Random Forest (RF) algorithm was used to predicted the AGB using different combination of variables. …”
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Panel regression method to analyse the stock market returns due to Covid-19 / Nur Mardziah Aziz Jaafar and Noraini Noordin by Aziz Jaafar, Nur Mardziah, Noordin, Noraini

“…This study aimed to determine the aftereffects of COVID-19 pandemic outbreaks on stock markets by measuring the correlation between market returns and daily growth of total new and death cases of COVID-19. Panel regression methods, namely pooled ordinary least square and fixed-effect methods were used in this study where the dependent variable is stock market returns and independent variables were i) daily growth new death cases COVID-19 ii) natural algorithm market capitalisation iii) Brent Crude Oil Price from January 2, 2020, until March 31, 2020. …”
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Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis by Adnani, Seyedeh Atena

“…In this system,similar insolvent system, three methods including one variable at a time, Taguchi method and ANN were used for optimization and prediction of percentage of conversion. …”
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Detection and Classification of Moving Objects for an Automated Surveillance System by Md. Tomari, Mohd Razali

“…The applied post processing module capable to remove noise and shadow from the detected objects with less than 1% of error. Finally, classification algorithm that makes use of the extracted moment values from the detected objects successfully categorize objects into pre-defined classes of human and vehicle with 89.08% of accuracy. …”
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Detection and classification of moving objects for an automated surveillance system by Md Tomari, Mohd Razali

“…The applied post processing module capable to remove noise and shadow from the detected objects with less than 1% of error. Finally, classification algorithm that makes use of the extracted moment values from the detected objects successfully categorize objects into pre-defined classes of human and vehicle with 89.08% of accuracy. …”
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Detection and classification of moving objects for an automated surveillance system by Md Tomari, Mohd Razali

“…The applied post processing module capable to remove noise and shadow from the detected objects with less than 1% of error. Finally, classification algorithm that makes use of the extracted moment values from the detected objects successfully categorize objects into pre-defined classes of human and vehicle with 89.08% of accuracy. …”
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