Search Results - (( (variable OR variables) deviation selection algorithm ) OR ( java application tools algorithm ))

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  1. 1

    Fault diagnostic algorithm for precut fractionation column by Heng, H. Y., Ali, Mohamad Wijayanuddin, Kamsah, Mohd. Zaki

    Published 2004
    “…Hazard and Operability Study (HAZOP) is used to support the diagnosis task. The algorithm has been successful in detecting the deviations of each variable by testing the data set. …”
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    Conference or Workshop Item
  2. 2

    Enhancing Model Selection Based On Penalized Regression Methods And Empirical Mode Decomposition by Al Jawarneh, Abdullah Suleiman Saleh

    Published 2021
    “…The penalized regularization methods are statistical techniques used to regularize and select the necessary predictor variables that have substantial effects on the response variable. …”
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    Thesis
  3. 3

    Fault diagnostic advisory system using moving-range chart and hazard operability study. by Heng, Han Yann, Ali, Mohamad Wijayanuddin, Kamsah, Mohd Zaki

    Published 2007
    “…Although the scheme was developed based on precut fractionation column, the algorithm of fault detection and diagnosis can be extended to other chemical process by changing the x-MR chart and HAZOP study for each selected monitoring variables.…”
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    Article
  4. 4
  5. 5

    Fault diagnostic advisory system using moving-range chart and hazard operability study by Heng, Han Yann, Ali, Mohamed Wijayanuddin, Kamsah, Mohd. Zaki

    Published 2007
    “…Although the scheme was developed based on precut fractionation column, the algorithm of fault detection and diagnosis can be extended to other chemical process by changing the x-MR chart and HAZOP study for each selected monitoring variables…”
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    Article
  6. 6
  7. 7

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…The key is the trigger mechanism to the algorithm. Until the advent of the Internet, encryption was rarely used by the public, but was largely a military tool. …”
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    Final Year Project
  8. 8

    Artificial neural network modelling of photodegradation in suspension of manganese doped zinc oxide nanoparticles under visible-light irradiation by Abdollahi, Yadollah, Zakaria, Azmi, Sairi, Nor Asrina, Matori, Khamirul Amin, Masoumi, Hamid Reza Fard, Sadrolhosseini, Amir Reza, Jahangirian, Hossein

    Published 2014
    “…According to the indicator, the QP-4-8-1, IBP-4-15-1, BBP-4-6-1, and LM-4-10-1 were selected as the optimized topologies. Among the topologies, QP-4-8-1 has presented the minimum RMSE and absolute average deviation as well as maximum R-squared. …”
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    Article
  9. 9

    The employment of support vector machine to classify high and low performance archers based on bio-physiological variables by Taha, Z., Musa, R.M., Majeed, A.P.P.A, Abdullah, M.R., Abdullah, M.A., Hassan, M.H.A., Khalil, Z.

    Published 2018
    “…The findings of this investigation can be valuable to coaches and sports managers to recognise high potential athletes from the selected bio-physiological variables examined.…”
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    Conference or Workshop Item
  10. 10

    Variable Neighbourhood Search Algorithm for Vehicle Routing Problem with Backhaul by Siaw Ying Doreen, Sek

    Published 2023
    “…Thus, a heuristic approach based on the Variable Neighbourhood Search (VNS) is proposed. In this research, 22 sets of benchmark instances introduced by Goetschalckx and Jacobs-Blecha are used to test the efficiency and effectiveness of the proposed algorithm. …”
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    Thesis
  11. 11

    The Identification of High Potential Archers Based on Fitness and Motor Ability Variables: A Support Vector Machine Approach by Zahari, Taha, Rabiu Muazu, Musa, Anwar, P. P. Abdul Majeed, Muhammad Muaz, Alim, Mohamad Razali, Abdullah

    Published 2018
    “…The present study classified and predicted high and low-potential archers from a set of fitness and motor ability variables trained on different SVMs kernel algorithms. 50 youth archers with the mean age and standard deviation of 17.0 ± 0.6 years drawn from various archery programmes completed a six arrows shooting score test. …”
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    Article
  12. 12

    Development of a rule-based fault diagnostic advisory system for precut fractionation column by Heng, Han Yann

    Published 2005
    “…Although the scheme was developed based on data of fatty acid precut fractionation column, the algorithm of fault detection and diagnosis can be extended to other chemical process by changing the x-MR chart and HAZOP for each selected monitoring variables.…”
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    Thesis
  13. 13
  14. 14

    Penalized LAD-SCAD estimator based on robust wrapped correlation screening method for high dimensional models by Baba, Ishaq Abdullahi, Midi, Habshah, Leong, Wah June, Ibragimov, Gafurjan I.

    Published 2021
    “…The SIS method uses the rank correlation screening (RCS) algorithm in the pre-screening step and the traditional Pathwise coordinate descent algorithm for computing the sequence of the regularization parameters in the post screening step for onward model selection. …”
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    Article
  15. 15

    The employment of Support Vector Machine to classify high and low performance archers based on bio-physiological variables by Zahari, Taha, Musa, Rabiu Muazu, Anwar, P. P. Abdul Majeed, Mohamad Razali, Abdullah, Muhammad Amirul, Abdullah, M. H. A., Hassan, Zubair, Khalil

    Published 2018
    “…The findings of this investigation can be valuable to coaches and sports managers to recognise high potential athletes from the selected bio-physiological variables examined.…”
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    Conference or Workshop Item
  16. 16

    The identification of high potential archers based on relative psychological coping skills variables: a support vector machine approach by Taha, Z., Musa, R.M., Majeed, A.P.P.A, Abdullah, M.R., Zakaria, M.A., Alim, M.M., Jizat, J.A.M., Ibrahim, M.F.

    Published 2018
    “…The findings of this investigation can be valuable to coaches and sports managers to recognise high potential athletes from the selected psychological coping skills variables examined which would consequently save time and energy during talent identification and development programme.…”
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    Conference or Workshop Item
  17. 17

    Optimal Reactive Power Dispatch Solution by Loss Minimization Using Moth-Flame Optimization Technique by Rebecca Ng, Shin Mei, Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Hamdan, Daniyal

    Published 2017
    “…The statisticalanalysis of this research illustrated that MFO is able to produce competitive results by yielding lowerpower loss and lower voltage deviation than the selected techniques from literature.…”
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    Article
  18. 18

    Model input and structure selection in multivariable dynamic modeling of batch distillation column pilot plant / Ilham Rustam by Rustam, Ilham

    Published 2015
    “…Comparison results have shown that the pre-screening method has an essential role in determining an effective process representation especially in real-time multivariable identification framework where a priori knowledge is not available and would help in resultant model generalization performance as opposed to simply using all available model input variables. Further, after a careful investigation into the OLS algorithm, it was shown that the ERR technique which is an essential part of the algorithm to reach model parsimony, has led the resultant model to select an incorrect model terms albeit some improvement in model selection criteria and validation method adopted in this study. …”
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    Thesis
  19. 19

    The identification of high potential archers based on relative psychological coping skills variables: A Support Vector Machine approach by Zahari, Taha, Rabiu Muazu, Musa, Anwar, P. P. Abdul Majeed, Mohamad Razali, Abdullah, Muhammad Aizzat, Zakaria, Muhammad Muaz, Alim, Jessnor Arif, Mat Jizat, Mohamad Fauzi, Ibrahim

    Published 2018
    “…The findings of this investigation can be valuable to coaches and sports managers to recognise high potential athletes from the selected psychological coping skills variables examined which would consequently save time and energy during talent identification and development programme.…”
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    Conference or Workshop Item
  20. 20

    A machine learning approach of predicting high potential archers by means of physical fitness indicators by Muazu Musa, Rabiu, Abdul Majeed, Anwar P.P., Taha, Zahari, Chang, Siow Wee, Ab. Nasir, Ahmad Fakhri, Abdullah, Mohamad Razali

    Published 2019
    “…The present study classified and predicted high and low potential archers from a set of physical fitness variables trained on a variation of k-NN algorithms and logistic regression. 50 youth archers with the mean age and standard deviation of (17.0 ± 0.56) years drawn from various archery programmes completed a one end archery shooting score test. …”
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    Article