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  1. 1
    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares

    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

    Published 2009
    “…The Ordinary Least Squares (OLS) method is often used to estimate the parameters of a linear model. …”
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  2. 2
    Dynamic robust bootstrap method based on LTS estimators

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

    Published 2009
    “…We call this method Dynamic Robust Bootstrap-LTS based (DRBLTS) because here we have employed the LTS estimator in the modified bootstrap algorithm. …”
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  3. 3
    Kalman filter based impedance parameter estimation for transmission line and distribution line

    Kalman filter based impedance parameter estimation for transmission line and distribution line by Siti Nur Aishah, Mohd Amin

    Published 2019
    “…This research also reports the performance of Kalman Filter method in transmission line compared with the other methods such as Linear Least Square method and Synchronous Phasor Measurement method. …”
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  4. 4
    Coordinate-Descent Adaptation over Hamiltonian Multi-Agent Networks

    Coordinate-Descent Adaptation over Hamiltonian Multi-Agent Networks by Azam Khalili, Vahid Vahidpour, Amir Rastegarnia, Ali Farzamnia, Teo, Kenneth Tze Kin, Saeid Sanei

    Published 2021
    “…The incremental least-mean-square (ILMS) algorithm is a useful method to perform distributed adaptation and learning in Hamiltonian networks. …”
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  5. 5
    Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli

    Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli by Ahmad Kamaruddin, Saadi, Md. Ghani, Nor Azura, Mohamed Ramli, Norazan

    Published 2014
    “…The backpropagation algorithm is one of the most famous algorithms to train neural network based on the mean square error (MSE) of ordinary least squares (OLS). …”
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  6. 6
    Estimation of Information Measures for Power-Function Distribution in Presence of Outliers and Their Applications

    Estimation of Information Measures for Power-Function Distribution in Presence of Outliers and Their Applications by Hassan, Amal Soliman, Elsherpieny, Elsayed Ahmed, Mohamed, Rokaya Elmorsy

    Published 2022
    “…The Bayesian estimators were computed empirically using a Monte Carlo simulation based on the Gibbs sampling algorithm. …”
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  7. 7
    Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering

    Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering by Davari, Atefeh, Marhaban, Mohammad Hamiruce, Mohd Noor, Samsul Bahari, Karimadini, Mohammad, Karimoddini, Ali

    Published 2011
    “…This is achieved by a pre-estimation using fuzzy clustering that provides a prior knowledge and forms a rough model to be fine tuned using the least square method. …”
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  8. 8
    The comparison study among optimization techniques in optimizing a distribution system state estimation

    The comparison study among optimization techniques in optimizing a distribution system state estimation by Hazim Imad, Hazim

    Published 2017
    “…This thesis introduce an intelligent decentralized State Estimation method based on Firefly algorithm for distribution power systems. …”
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  9. 9
    Tracking moving targets in wireless sensor networks using extended diffusion strategies of distributed Kalman filter

    Tracking moving targets in wireless sensor networks using extended diffusion strategies of distributed Kalman filter by Solouk, Vahid, Taghizadeh, Hamid, Moghanjoughi, Ayyoub Akbari, Razm, S. K.

    Published 2013
    “…The proposed algorithms provide precise state estimates in a moment as global state estimates using various updates at each step. …”
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  10. 10
    Bayesian survival and hazard estimates for Weibull regression with censored data using modified Jeffreys prior

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

    Published 2013
    “…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. …”
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  11. 11
    Accuracy enhancement for zone mapping of a solar radiation forecasting based multi-objective model for better management of the generation of renewable energy

    Accuracy enhancement for zone mapping of a solar radiation forecasting based multi-objective model for better management of the generation of renewable energy by Ehteram M., Ahmed A.N., Fai C.M., Afan H.A., El-Shafie A.

    Published 2023
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  12. 12
    Modified sequential fences for identifying univariate outliers

    Modified sequential fences for identifying univariate outliers by Wong, Hui Shein

    Published 2016
    “…In addition, this proposed method also estimates trimmed mean and trimmed standard deviation with smaller bias and smaller root of mean squares error. …”
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  13. 13
    Robust Kernel Density Function Estimation

    Robust Kernel Density Function Estimation by Dadkhah, Kourosh

    Published 2010
    “…The classical kernel density estimation technique is the commonly used method to estimate the density function. …”
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  14. 14
    Integration of machine learning and remote sensing for above ground biomass estimation through Landsat-9 and field data in temperate forests of the Himalayan region

    Integration of machine learning and remote sensing for above ground biomass estimation through Landsat-9 and field data in temperate forests of the Himalayan region by Anees, Shoaib Ahmad, Mehmood, Kaleem, Khan, Waseem Razzaq, Sajjad, Muhammad, Alahmadi, Tahani Awad, Alharbi, Sulaiman Ali, Luo, Mi

    Published 2024
    “…Secondly, the research systematically assesses the effectiveness of different algorithms to identify the most precise method for establishing any potential relationship between field-measured AGB and predictor variables. …”
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  15. 15
    Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model

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

    Published 2000
    “…A generated data where the failure times were taken as exponentially distributed was used to further compare these two methods of estimation. …”
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  16. 16
    Estimation of transformers health index based on condition parameter factor and hidden Markov model

    Estimation of transformers health index based on condition parameter factor and hidden Markov model by Mohd Selva, Amran, Yahaya, Muhammad Sharil, Azis, Norhafiz, Ab Kadir, Mohd Zainal Abidin, Jasni, Jasronita, Yang Ghazali, Young Zaidey

    Published 2018
    “…Next, the emission probabilities for each of the condition parameter factors were derived based on frequency of occurrence method. Subsequently, the future states probability distribution was computed based on the HMM prediction model and viterbi algorithm was applied to find the best optimal path sequence of HI for the respective observable condition. …”
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  17. 17
    Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis

    Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis by Mohamed Elfaki, Faiz Ahmed

    Published 2004
    “…The Expectation Maximization (EM) algorithm is utilized to obtain the estimate of the parameters in the models. …”
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  18. 18
    Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar

    Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar by Seyed Alireza, Ravanfar

    Published 2017
    “…However, most of existing damage detection methods requires reference data which are not always available. …”
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  19. 19
    Statistical modelling of time series of counts for a new class of mixture distributions / Khoo Wooi Chen

    Statistical modelling of time series of counts for a new class of mixture distributions / Khoo Wooi Chen by Khoo, Wooi Chen

    Published 2016
    “…The iv score functions and information matrix have been derived to measure the asymptotic standard errors and to analyze the variance-covariance relationship among the parameters. Parameter estimation with the maximum likelihood estimation via the Expectation-Maximization algorithm is discussed and compared with the conditional least squares method. …”
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  20. 20
    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani

    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani by Ehsan Taslimi , Renani

    Published 2018
    “…In this method, firstly, Weibull density function is utilized to model the wind speed and then several methods are applied to estimate the parameters of the wind speed distribution. …”
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