Search Results - (( learning implementation using algorithm ) OR ( parameter estimation based algorithm ))

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  1. 1

    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. …”
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  2. 2

    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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  3. 3

    Active force control with iterative learning control algorithm for a vehicle suspension by Rosmazi, Rosli

    Published 2013
    “…ILC algorithm is implemented into AFC-based control scheme to reduce its complexity and hence faster response, by replacing the use of artificial intelligence (Al) method as proposed by previous researcher. …”
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  4. 4

    Q-learning based vertical handover decision algorithm in LTE-A two-tier macrocell-femtocell systems / Ammar Bathich by Bathich, Ammar

    Published 2019
    “…The main objective of this work is to propose and implement an efficient handover decision procedure based on users’ profiles using Q-learning technique in a LTE-A macrocell-femtocell networks. …”
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  5. 5

    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

    Published 2021
    “…Multi-Verse Optimizer (MVO) is one of the most recent robust nature-inspired metaheuristic algorithm. It has been successfully implemented and used in various areas such as machine learning applications, engineering applications, network applications, parameter control, and other similar applications to solve optimization problems. …”
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  6. 6

    Restoration of blurred images using geometric and chebichef moments / Ahlad Kumar by Ahlad, Kumar

    Published 2016
    “…Once the blur parameters are estimated, image restoration of the proposed method is carried out using split Bregman algorithm. …”
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  7. 7

    Application of Machine Learning and Deep Learning Algorithms for Landslide Susceptibility Assessment in Landslide Prone Himalayan Region by Bhattacharya S., Ali T., Chakravortti S., Pal T., Majee B.K., Mondal A., Pande C.B., Bilal M., Rahman M.T., Chakrabortty R.

    Published 2025
    “…This study employs various machine learning and deep learning algorithms, specifically Random Forest (RF), Artificial Neural Network (ANN), and Deep Learning Neural Network (DLNN), to estimate landslide susceptibility in Chamoli district, Uttarakhand, India?…”
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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 hybrid Wavelet Multiresolution Analysis and Machine learning algorithm (WMRA-ML) is used to extracts the useful hidden knowledge from decomposed one-cycle fault transient signals (voltage & current) from four Matlab/Simulink CIGRE models. …”
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    An optimized ensemble for predicting reservoir rock properties in petroleum industry by Kenari, Seyed Ali Jafari

    Published 2013
    “…A lot of researches have been done to predict the reservoir parameters using well log data through applying various methods. …”
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  13. 13

    Experimental analysis and data-driven machine learning modelling of the minimum ignition temperature (MIT) of aluminium dust by Arshad, U., Taqvi, S.A.A., Buang, A.

    Published 2022
    “…Based on the statistical nature of the dust explosions and controlling parameters, this study uses data-driven modelling approaches. …”
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  14. 14

    Experimental analysis and data-driven machine learning modelling of the minimum ignition temperature (MIT) of aluminium dust by Arshad, U., Taqvi, S.A.A., Buang, A.

    Published 2022
    “…Based on the statistical nature of the dust explosions and controlling parameters, this study uses data-driven modelling approaches. …”
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    Article
  15. 15

    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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  16. 16

    Finite impulse response optimizers for solving optimization problems by Ab Rahman, Tasiransurini

    Published 2019
    “…In this work, three new estimation-based metaheuristic algorithms are introduced. …”
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  17. 17

    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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  18. 18

    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

    Published 2011
    “…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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    Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

    Published 2019
    “…In this work, three new estimation-based metaheuristic algorithms are introduced. …”
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    Thesis