Search Results - processes estimation ((method algorithm) OR (means algorithm))

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  1. 1

    Segmentation of MRI brain images using statistical approaches by Balafar, Mohammad Ali

    Published 2011
    “…Noise is one of the obstacles for brain MRI segmentation. The non-Local means (NL-means) algorithm is a state-of-the art neighbourhood-based noisereduction method which is time-consuming and its accuracy can be improved. …”
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    Thesis
  2. 2

    Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm by Dalatu, Paul Inuwa

    Published 2018
    “…It is attained successfully by combining the mean in K-Means algorithm, minimum and maximum in K-Midranges algorithm and compute their average as mean cluster of Hybrid mean. …”
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    Thesis
  3. 3

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

    Published 2016
    “…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.…”
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    Article
  4. 4

    Noise Reduction using Mean Shift Algorithm for Estimating 3D Shape by Malik , Aamir Saeed, Shim, Seongo, Choi, Tae-Sun

    Published 2011
    “…In this paper, we propose a method based on mean shift algorithm to remove noise introduced by the imaging process while minimizing loss of edges. …”
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    Citation Index Journal
  5. 5
  6. 6

    An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems by Remli, Muhammad Akmal, Mohamad, Mohd Saberi, Deris, Safaai, Sinnott, Richard, Napis, Suhaimi

    Published 2019
    “…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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    Article
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  8. 8

    A Computationally Efficient Least Square Channel Estimation Method for MIMO-OFDM Systems by Ahmad, Hasan, Motakabber, S. M. A., Anwar, Farhat, Habaebi, Mohamed Hadi, Ibrahimy, Muhammad Ibn

    Published 2021
    “…Some of the most popular methods used in cellular communication for channel estimation are the Least Squares (LS) algorithm and the Minimum Mean Square Error (MMSE) algorithm. …”
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    Proceeding Paper
  9. 9

    A decision support system using Neurofuzzy algorithm methods in selecting lecturer's teaching work load for bachelor in multimedia / Asmaa Musa by Musa, Asmaa

    Published 2007
    “…A key stage in the system process is the selection of features. This paper discuss about a decision support system using Neurofuzzy algorithm methods in selecting lecturer's teaching work load for Bachelor in Multimedia. …”
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    Thesis
  10. 10

    Digital quadrature compensators scheme for analog imperfections of quadrature modulator in wireless communication systems by Talebpour, Faraz

    Published 2016
    “…It will also result in increasing the number of iteration required to estimate the channel values In the proposed schemes, the problem of channel estimation accuracy for an adaptive algorithm named “least mean square algorithm” (LMS) with one feedback is avoided via a two feedback scheme. …”
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    Thesis
  11. 11

    Augmented model based double iterative loop techniques for integrated system optimisation and parameter estimation of large scale industrial processes by Normah Abdullah, Brdys, M.A., Roberts, P.D.

    Published 1993
    “…This means that the algorithms use available information from the real process efficiently and a significant reduction in set-point alterations to real subprocesses is achieved. …”
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    Article
  12. 12

    GMSD-based perceptually motivated non-local means filter for image denoising by Baqar, Mohtashim *, Lau, Sian Lun *

    Published 2019
    “…Further, the proposed methodology also helps in mitigating the patch jittering blur effect (PJBE) and over smoothing of denoised images as observed with conventional NLM algorithm. Experimental evaluations based on visual-quality assessment and least-square based metrics have shown that the proposed algorithm yields better denoised image estimates than the conventional NLM algorithm. …”
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    Conference or Workshop Item
  13. 13

    Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA) by Ainul, H. M. Y., Salleh, S. M., Halib, N., Taib, H., Fathi, M. S.

    Published 2018
    “…In this paper, optimization technique was applied to optimize the objective function that lead to satisfying solution which obtain the dynamic model of the system. Realcoded genetic algorithm (RCGA) as a stochastic global search method was applied for optimization. …”
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    Article
  14. 14

    Estimating Marine CSEM Responses Using Gaussian Process Regression Based on Synthetic Models by Mohd Aris, M.N., Daud, H., Mohd Noh, K.A., Dass, S.C.

    Published 2022
    “…Current practice for processing marine CSEM responses utilizes meshes-based algorithms. …”
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    Article
  15. 15

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

    Published 2016
    “…The multi-class classification strategy is used to ensure quick estimation of the multi-class NN algorithms. All of the algorithms are later combined to provide device location estimation for multi-floor environment. …”
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    Thesis
  16. 16

    Sure (EM)-Autometrics: An Automated Model Selection Procedure with Expectation Maximization Algorithm Estimation Method (S/O 14925) by Kamarudin, Nur Azulia

    Published 2021
    “…Hence, this study concentrates on an automated model selection procedure for the SURE model by integrating the expectation-maximization (EM) algorithm estimation method, named SURE(EM)-Autometrics. …”
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    Monograph
  17. 17

    Performance comparison of feedforward neural network training algorithms in modeling for synthesis of polycaprolactone via biopolymerization by Wong, Yong Jie, Arumugasamy, Senthil Kumar, Jewaratnam, Jegalakshimi

    Published 2018
    “…This paper compares mean absolute error, mean square error, and mean absolute percentage error (MAPE) in the PCL biopolymerization process for 11 different training algorithms that belong to six classes, namely (1) additive momentum, (2) self-adaptive learning rate, (3) resilient backpropagation, (4) conjugate gradient backpropagation, (5) quasi-Newton, and (6) Bayesian regulation propagation. …”
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    Article
  18. 18

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

    Published 2014
    “…Those algorithms which performed estimation carrying out lots of calculation that leads in expensive methods in terms of computing resources. …”
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    Thesis
  19. 19

    Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA) by Ainul, H. M. Y., Salleh, S. M., Halib, N., Taib, H., Fathi, M. S.

    Published 2024
    “…In this paper, optimization tech-nique was applied to optimize the objective function that lead to satisfying solution which obtain the dynamic model of the system. Real-coded genetic algorithm (RCGA) as a stochastic global search method was applied for optimization. …”
    Article
  20. 20

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

    Published 2018
    “…It can be concluded that the modified algorithm decreases the biases, the variances and the mean squared errors of the LTS estimators. …”
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    Thesis