Search Results - (( parameter estimation method algorithm ) OR ( data normalization based algorithm ))*

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  1. 1
    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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  2. 2
    PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah

    PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah by Abdullah, Siti Muniroh

    Published 2017
    “…Results suggest that the PSO algorithm is viable alternative to other established algorithms for LLS parameter estimation. …”
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  3. 3
    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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  4. 4
    Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems

    Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems by Marzook, Ali Kamil, Ismail, Alyani, Mohd Ali, Borhanuddin, Sali, Aduwati, Khalaf, Mohannad H., Khatun, Sabira

    Published 2013
    “…We exploit the rank deficient of H to reduce the number of parameters that characterizes this matrix. The adopted reduced rank technique is based on singular value decomposition algorithm. …”
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  5. 5
    Reduced-rank technique for joint channel estimation in TD-SCDMA systems.

    Reduced-rank technique for joint channel estimation in TD-SCDMA systems. by Ismail, Alyani, Sali, Aduwati, Mohd Ali, Borhanuddin, Khatun, Sabira

    Published 2013
    “…We exploit the rank deficient of H to reduce the number of parameters that characterizes this matrix. The adopted reduced rank technique is based on singular value decomposition algorithm. …”
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  6. 6
    Reduced Rank Technique for Joint Channel Estimation and Joint Data Detection in TD-SCDMA Systems

    Reduced Rank Technique for Joint Channel Estimation and Joint Data Detection in TD-SCDMA Systems by Sabira, Khatun, Ali K., Marzook, Alyani, Ismail, Aduwati, Sali, Mohannad Hamed, Khalaf, Borhan, M. Ali

    Published 2012
    “…We exploit the rank deficient of H to reduce the number of parameters that characterizes this matrix. The adopted reduced rank technique is based on singular value decomposition algorithm. …”
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  7. 7
    Modified least trimmed squares method for face recognition / Nur Azimah Abdul Rahim

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

    Published 2018
    “…The genetic algorithm configuration for n (number of observations) and p (parameter) was changed to assess the performance of modified method. …”
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  8. 8
    Particle filter approach for tracking indoor user location using IEEE 802.11 signals

    Particle filter approach for tracking indoor user location using IEEE 802.11 signals by Mantoro, Teddy, Ayu, Media Anugerah, Raman, Shakiratul Husna, Latiff , N. H. M.

    Published 2011
    “…The paper discussed the comparison between the true location and the estimated location based on two types of signals data: normal data and noise data. …”
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  9. 9
    Particle filter approach for estimating indoor mobile user location using IEEE 802.11 signals (F1090)

    Particle filter approach for estimating indoor mobile user location using IEEE 802.11 signals (F1090) by Mantoro, Teddy, Ayu, Media Anugerah, Raman, Shakiratul Husna, Md. Latiff , Nurul Hidayati

    Published 2011
    “…The paper discussed the comparison between the true location and the estimated location based on two types of signals data: normal data and noise data. …”
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  10. 10
    Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms

    Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

    Published 2020
    “…Firstly, an improved EM (IEM) algorithm is presented to estimate the five parameters of the single PV-module system. …”
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  11. 11
    Application of Evolutionary Algorithm for Assisted History Matching

    Application of Evolutionary Algorithm for Assisted History Matching by Zahari, Muhammad Izzat

    Published 2014
    “…Today, tremendous efforts are made to develop Automatic History Matching algorithms. While the automatic method focus on optimization which is normally computer based. …”
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    Final Year Project
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  12. 12
    Fraud detection in telecommunication using pattern recognition method / Mohd Izhan Mohd Yusoff

    Fraud detection in telecommunication using pattern recognition method / Mohd Izhan Mohd Yusoff by Mohd Yusoff, Mohd Izhan

    Published 2014
    “…Due to the complexity of GMM, we use Expectation Maximization (or EM) algorithm by Dempster et al. (1977) to obtain the maximum likelihood estimates of the GMM parameters. …”
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  13. 13
    Rank-based inference for the accelerated failure time model in the presence of interval censored data

    Rank-based inference for the accelerated failure time model in the presence of interval censored data by Karimi, Mostafa, Ibrahim, Noor Akma, Abu Bakar, Mohd Rizam, Arasan, Jayanthi

    Published 2016
    “…In this paper a class of asymptotically normal rank estimators is developed which can be aquired via linear programming for estimating the parameters of the model, and a two-step iterative algorithm is introduce for solving the estimating equations. …”
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  14. 14
    Interpolation and Extrapolation Techniques Based Neural Network in Estimating the Missing Ionospheric TEC Data

    Interpolation and Extrapolation Techniques Based Neural Network in Estimating the Missing Ionospheric TEC Data by Jayapal, V, Zain, AFM

    Published 2024
    Proceedings Paper
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  15. 15
    Interpolation and extrapolation techniques based Neural Network in estimating the missing ionospheric TEC data

    Interpolation and extrapolation techniques based Neural Network in estimating the missing ionospheric TEC data by Jayapal V., Zain A.F.M.

    Published 2024
    “…Normalized RMSE, RMSE and relative correction are computed for both methods to evaluate the capability of NN to interpolate and extrapolate the missing data. …”
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  16. 16
    Robust estimation methods for fixed effect panel data model having block-concentrated outliers

    Robust estimation methods for fixed effect panel data model having block-concentrated outliers by Abu Bakar @ Harun, Nor Mazlina

    Published 2019
    “…The Ordinary Least Squares (OLS) is the commonly used method to estimate the parameters of fixed effect panel data model. …”
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  17. 17
    The largest studentized residual test for bad data identification in state estimation of a power system

    The largest studentized residual test for bad data identification in state estimation of a power system by Khan, Z., Razali, R.B., Daud, H., Nor, N.M., Firuzabad, M.F.

    Published 2015
    “…The presence of systematic errors can alter the results of state estimation. The chi-square and normalized residual tests are the common post estimation procedures usually used for detection and identification of gross errors in the estimation algorithm. …”
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  18. 18
    A new hybrid multiaxial fatigue life model based on critical plane continuum damage mechanics and genetic algorithm

    A new hybrid multiaxial fatigue life model based on critical plane continuum damage mechanics and genetic algorithm by Masood, Kamal

    Published 2015
    “…Material parameter including stress sensitivity factor for normal or shear stress can be incorporated to improve the calibration process. …”
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  19. 19
    Estimating Crack Effects on Electrical Characteristics of PV Modules Based on Monitoring Data and I-V Curves

    Estimating Crack Effects on Electrical Characteristics of PV Modules Based on Monitoring Data and I-V Curves by Feng L., Zhang J., Kiong T.S., Ding K., Amin N., Hamelmann F.U.

    Published 2024
    “…Meanwhile, an innovative parameter optimization algorithm based on particle swarm optimization is developed to extract the parameters. …”
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  20. 20
    Fault Detection and Identification in Quadrotor System (Quadrotor Robot)

    Fault Detection and Identification in Quadrotor System (Quadrotor Robot) by Chan, Shi Jing, Pebrianti, Dwi

    Published 2016
    “…The ANN is designed based on the back-propagation technique so that it can be trained to generate output based on the data. …”
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