Search Results - (( variable extractions path algorithm ) OR ( normal distribution methods algorithm ))

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  1. 1

    Improved performance in distributed estimation by convex combination of DNSAF and DNLMS algorithms by Ahmad Pouradabi, Amir Rastegarnia, Azam Khalili, Ali Farzamnia

    Published 2022
    “…Diffusion normalized least mean square (DNLMS) algorithm has low misadjustment error, but it is slow in convergence. …”
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    Proceedings
  2. 2

    Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

    Published 2004
    “…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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    Thesis
  3. 3

    A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

    Published 2005
    “…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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    Monograph
  4. 4

    Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan by Hassan, Siti Fatimah

    Published 2015
    “…For example, the distribution analogues to the normal distribution in linear data is known as circular normal distribution. …”
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    Thesis
  5. 5

    Statistical approach on grading: mixture modeling by Md. Desa, Zairul Nor Deana

    Published 2006
    “…Statistical approaches which use the Standard Deviation and conditional Bayesian methods are considered to assign the grades. In the conditional Bayesian model, we assume the data to follow the Normal Mixture distribution where the grades are distinctively separated by the parameters: means and proportions of the Normal Mixture distribution. …”
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    Thesis
  6. 6
  7. 7

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

    Published 2009
    “…One of the important assumptions of the linear model is that the error terms are normally distributed. Unfortunately, many researchers are not aware that the performance of the OLS can be very poor when the data set that one often makes a normal assumption, has a heavy-tailed distribution which may arise as a result of the presence of outliers. …”
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    Thesis
  8. 8

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

    Published 2009
    “…In order to make reliable inferences about the parameters of a model, require that the parameter estimates are normally distributed. Nevertheless, in real situations, many estimates are not normal and the use of bootstrap method is more appropriate as it does not rely on the normality assumption. …”
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    Article
  9. 9

    Statistical approach on grading the student achievement via normal mixture modeling by Md. Desa, Zairul Nor Deana, Mohamad, Ismail, Mohd. Khalid, Zarina, Md. Zin, Hanafiah

    Published 2006
    “…Statistical approaches which used the Standard Deviation (GC) and conditional Bayesian methods are considered to assign the grades. In the conditional Bayesian model, we assume the data to follow the Normal Mixture distribution where the grades are distinctively separated by the parameters: means and proportions of the Normal Mixture distribution. …”
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    Article
  10. 10

    The effect of dose calculation algorithms on the normal tissue complication probability values of thoracic cancer by Ahmad, Noor Ashikin

    Published 2015
    “…Purpose: To identify the effect of dose calculation algorithms on the Normal Tissue Complication Probability values of thoracic cancer. …”
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    Monograph
  11. 11

    Statistical approach on grading the student achievement via mixture modelling by Md. Desa, Zairul Nor Deana, Mohamad, lsmail

    Published 2006
    “…In the conditional Bayesian model, we assume the Normal Mixture distribution where the grades are distinctively separated means and proportions of the Normal Mixture distribution. …”
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    Article
  12. 12

    Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah by Abdullah, Mohd Azrul

    Published 2015
    “…Anderson-Darling (AD) and Goodness of Fit test is used to identify the best fitted distribution model to the real data. Four traffic distribution which are normal, lognormal, Weibull and exponential distribution are fitted and derived. …”
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    Article
  13. 13

    Omega grey wolf optimizer (ωGWO) for optimization of overcurrent relays coordination with distributed generation by Noor Zaihan, Jamal

    Published 2019
    “…The overall protection coordination is thus very complicated and could not be satisfied using the conventional method moreover for the modern distribution system. …”
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    Thesis
  14. 14

    Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah by Abdullah, Mohd Azrul

    Published 2015
    “…Anderson-Darling (AD) and Goodness of Fit test is used to identify the best fitted distribution model to the real data. Four traffic distribution which are normal, lognormal, Weibull and exponential distribution are fitted and derived. …”
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    Thesis
  15. 15
  16. 16

    Optimal placement and sizing of distributed generation in radial distribution networks using particle swarm optimization and forward backward sweep method by Lawal, Sani Mohammed

    Published 2012
    “…The proposed PSO algorithm is used to determine optimal placement and size of DG in radial distribution networks, where Forward Backward Sweep Method (FBSM) of distribution load flow analysis was used, to determine the actual power loss in the system. …”
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    Thesis
  17. 17

    Early detection and mitigation of DDoS attacks in software defined networks by Al-Saadi, Mustafa Yahya Zakariya

    Published 2018
    “…The entropy increased and came close to the normal traffic entropy. The proposed method in this project was able to detect and mitigate the attack effectively in its early stages before the intensity escalate to a degree that exhausts the controller. …”
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    Thesis
  18. 18

    Statistical performance of agglomerative hierarchical clustering technique via pairing of correlation-based distances and linkage methods by Nurshaziana, Mohamad Shamsuri

    Published 2025
    “…Five tables of summary for choosing appropriate clustering algorithms according to data distribution were produced. …”
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    Thesis
  19. 19

    Protection Coordination Toward Optimal Network Reconfiguration and DG Sizing by Abdul Rahim, Mohamad Norshahrani, Mokhlis, Hazlie, Bakar, Ab Halim Abu, Rahman, Mir Toufikur, Badran, Ola, Mansor, Nurulafiqah Nadzirah

    Published 2019
    “…Constraints on protection coordination and DG size are explicitly formulated in the proposed method. The validity of the proposed method is analyzed on three commonly used IEEE 33-bus, 69-bus and 118-bus distribution systems, employing the firefly algorithm (FA) and evolutionary programming (EP) algorithm. …”
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    Article
  20. 20

    Entropy in portfolio optimization / Yasaman Izadparast Shirazi by Yasaman Izadparast, Shirazi

    Published 2017
    “…The purpose of this new model is to overcome the limitations as observed in a traditional model; that is, having performance close to Markowitz’s mean-variance (MV) model when data comes from a normal distribution, but exhibit better performance when data comes from a non-normal distribution. …”
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    Thesis