Search Results - (( code classification _ algorithm ) OR ( parameter estimation system algorithm ))

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  1. 1

    Development of gender and race recognition system using speech and recognition by using frequency spectrum by Ng Siew Fong

    Published 2009
    “…In this thesis, the development of an algorithm and system that is able to recognize gender and races by using the speech frequency spectrum is presented. …”
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    Learning Object
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    Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line by Olufemi, Osaji Emmanuel

    Published 2020
    “…The relay operation setting compromise is due to the wrong estimated impedance seen by the relay leading to overreach or underreach mal-operation. …”
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    Thesis
  3. 3

    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
  4. 4

    A new metaphor-less algorithms for the photovoltaic cell parameter estimation by Premkumar M., Babu T.S., Umashankar S., Sowmya R.

    Published 2023
    “…Multiobjective optimization; Parameter estimation; Photoelectrochemical cells; Photovoltaic cells; Solar power generation; Cell parameter; Estimated parameter; Local minimums; Optimization algorithms; Pre-mature convergences; Solar cell parameters; Solar photovoltaic system; Solar PVs; Solar cells…”
    Article
  5. 5

    Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2014
    “…This paper presents a classification of android malware using candidate detectors generated from an unsupervised association rule of Apriori algorithm improved with particle swarm optimization to train three different supervised classifiers. …”
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    Proceeding Paper
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    Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2015
    “…However, supervised learning technique has limitations for malware classification task. This paper presents a classification approach on android malware using candidate detectors generated from an unsupervised association rule of Apriori Algorithm. …”
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    Article
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    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

    Published 2022
    “…Therefore, it is crucial to assess the parameter of chaotic systems. To solve the issue of parameter estimation for a chaotic system, deep learning is utilized. …”
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    Conference or Workshop Item
  9. 9

    Simultaneous Computation of Model Order and Parameter Estimation for System Identification Based on Gravitational Search Algorithm by Kamil Zakwan, Mohd Azmi, Pebrianti, Dwi, Zuwairie, Ibrahim, Shahdan, Sudin, Sophan Wahyudi, Nawawi

    Published 2015
    “…Both the model order and the parameters of the system are estimated simultaneously to attain the best mathematical model of a system. …”
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    Conference or Workshop Item
  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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    Railway wheelset parameter estimation using signals from lateral velocity sensor by Selamat, H., Alimin, A. J., Sam, Y.M.

    Published 2008
    “…A type of parameter estimation technique based on the linear integral filter (LIF) method, the least-absolute error with variable forgetting factor (LAE+VFF) estimation method, is proposed in this paper to estimate the railway wheelset parameters modelled as a time-varying continuous-time (C-T) system. …”
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    Article
  13. 13

    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
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    Parameter estimation of essential amino acids in Arabidopsis thaliana using hybrid of bees algorithm and harmony search by Aw, Mei Yee, Mohd Saberi, Mohamad, Chong, Chuii Khim, Safaai, Deris, Muhammad Akmal, Remli, Mohd Arfian, Ismail, Corchado, Juan Manuel, Omatu, Sigeru

    Published 2019
    “…Mathematical models of metabolic processes are the cornerstone of computational systems biology. In model building, the task of parameter estimation is difficult due to the huge numbers of kinetics parameters involved. …”
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    Book Chapter
  18. 18

    Orthogonal least square algorithm and its application for modelling suspension system by Ahmad, Robiah, Jamaluddin, Hishamuddin

    Published 2001
    “…Modelling based on input and output data is known as system identification. One of the issues in system identification is the parameter estimation and model structure selection where various methods have been studied including the orthogonal least square algorithm. …”
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    Article
  19. 19

    ADAPTIVE LINEAR ALGORITHMS FOR POWER SYSTEM FUNDAMENTAL AND HARMONIC ESTIMATION by MUBARAK MOHMMED, HUSSAM ALHAJ

    Published 2015
    “…Several approaches have been presented in the last two decades to estimate the fundamental frequency and harmonics. The most popular algorithm that has been implemented to estimate, and quantify power system fundamental frequency and harmonic components is the Fast Fourier Transform (FFT). …”
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    Thesis
  20. 20

    Mixed Unscented Kalman Filter and differential evolution for parameter identification by Legowo, Ari, Mohamad, Zahratu H., Park, HoonCheol

    Published 2013
    “…UKF have known to be a typical estimation technique used to estimate the state vectors and parameters of nonlinear dynamical systems and DE is one of the most powerful stochastic real-parameter optimization algorithms. …”
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    Article