Search Results - (( parameter estimation method algorithm ) OR ( fraud detection method algorithm ))*

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  1. 1

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

    Published 2014
    “…The new algorithm is tested on simulated and real data where the results show it is capable of detecting fraud activities. …”
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    Thesis
  2. 2

    Fraud detection in telecommunication industry using Gaussian mixed model by Mohd Yusoff, Mohd Izhan, Mohamed, Ibrahim, Abu Bakar, Mohd Rizam

    Published 2013
    “…The expectation maximization algorithm is used to estimate the parameter of the model such that the initial values of the algorithm is determined using the kernel method. …”
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    Conference or Workshop Item
  3. 3

    Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

    Published 2023
    “…It provides an increased convergence and globally optimized solutions. The algorithm has been tested using actual customer consumption data from SESB. 10 fold cross validation method is used to confirm the consistency of the detection accuracy. …”
    Conference Paper
  4. 4

    Credit Card Fraud Detection Using AdaBoost and Majority Voting by Randhawa, Kuldeep, Loo, Chu Kiong, Seera, Manjeevan, Lim, Chee Peng, Nandi, Asoke K.

    Published 2018
    “…In this paper, machine learning algorithms are used to detect credit card fraud. Standard models are first used. …”
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    Article
  5. 5

    Improved expectation maximization algorithm for Gaussian mixed model using the kernel method by Mohd Yusoff, Mohd Izhan, Mohamed, Ibrahim, Abu Bakar, Mohd Rizam

    Published 2013
    “…Finally, for illustration, we apply the improved algorithm to real telecommunication data. The modified method will pave the way to introduce a comprehensive method for detecting fraud calls in future work.…”
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    Article
  6. 6

    Employing Artificial Intelligence to Minimize Internet Fraud by Wong, E.S.K.

    Published 2009
    “…Following this, an a ttempt is made to propose using the MonITARS (Monitoring In sider Trading and Regulatory Surveillance) Systems framework which uses a combination of genetic algorithms, neural nets and statistical analysis in detecting insider dealing, to be used in the detection of transaction fraud. …”
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    Article
  7. 7

    Semiparametric inference procedure for the accelarated failure time model with interval-censored data by Karimi, Mostafa

    Published 2019
    “…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
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  8. 8

    Outlier Detection Technique in Data Mining: A Research Perspective by Mansur, M. O., Md. Sap, Mohd. Noor

    Published 2005
    “…The identification of outliers can lead to the discovery of unexpected knowledge in areas such as credit card fraud detection, calling card fraud detection, discovering criminal behaviors, discovering computer intrusion, etc. …”
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    Conference or Workshop Item
  9. 9
  10. 10

    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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    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse) by Jia, Xing Yeoh, Chuii, Khim Chong, Mohd Saberi, Mohamad, Yee, Wen Choon, Lian, En Chai, Safaai, Deris, Zuwairie, Ibrahim

    Published 2015
    “…The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimisation method implemented to obtain the best kinetic parameter value. …”
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    Article
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    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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    Thesis
  16. 16

    Parameter estimation of tapioca starch hydrolysis process: application of least squares and genetic algorithm by Rashid, Roslina, Jamaluddin, Hishamuddin, Saidina Amin, Nor Aishah

    Published 2005
    “…The performance of genetic algorithm (GA) in nonlinear kinetic parameter estimation of topiaca starch hydrolysis was studied and compared with Gauss-Newton method. …”
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    Article
  17. 17

    A voting-based hybrid machine learning approach for fraudulent financial data classification / Kuldeep Kaur Ragbir Singh by Kuldeep Kaur , Ragbir Singh

    Published 2019
    “…The empirical results positively indicate that the hybrid model with the sliding window method is able to yield a good accuracy rate of 82.4% in detecting fraud cases in real world credit card transactions. …”
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  18. 18

    Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail by Foo, Fong Yeng, Lau, Gee Choon, Ismail, Zuhaimy

    Published 2014
    “…The objective of this research is to estimate the Double Exponential Smoothing by using Genetic Algorithm Mechanism. …”
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    Research Reports
  19. 19

    Estimation in spot welding parameters using genetic algorithm by Lukman, Hafizi

    Published 2007
    “…By using Genetic algorithm (GA) the spot welding parameters can be estimated.…”
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    Thesis
  20. 20

    Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor by Adilah, Abdul Ghapor

    Published 2017
    “…This study begins by proposing a robust technique for estimating the slope parameter in LFRM. In particular, the focus is on the non-parametric estimation of the slope parameter and the robustness of this technique is compared with the maximum likelihood estimation and the Al-Nasser and Ebrahem (2005) method. …”
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    Thesis