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  1. 1
    Design and implemtation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayyawi

    Design and implemtation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayyawi by Jabbar Hayyawi, Mustafa

    Published 2016
    “…Performance indices such as workspace, dexterity and stiffness, of the parallel manipulator are studied. The parallel manipulator is optimized based on the performance indices to obtain on the optimal design parameters for achieved maximum performance of the parallel manipulator. …”
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  2. 2
    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms

    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms by Loo, C.K., Liew, W.S., Seera, M., Lim, Einly

    Published 2015
    “…A genetic algorithm search heuristic was chosen to solve this multi-objective optimization problem. …”
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  3. 3
    Design and implementation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayawi

    Design and implementation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayawi by Hayawi, Mustafa Jabbar

    Published 2015
    “…Performance indices such as workspace, dexterity and stiffness, of the parallel manipulator are studied. The parallel manipulator is optimized based on the performance indices to obtain on the optimal design parameters for achieved maximum performance of the parallel manipulator. …”
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  4. 4
    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach

    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
    “…The most popular method to solve parameter estimation problem is using optimization algorithm that easily trap to local minima and poor in exploitation to find the good solutions. …”
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  5. 5
    PMT : opposition based learning technique for enhancing metaheuristic algorithms performance

    PMT : opposition based learning technique for enhancing metaheuristic algorithms performance by Hammoudeh, S. Alamri

    Published 2020
    “…Metaheuristic algorithms have shown promising performance in solving sophisticated real-world optimization problems. …”
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  6. 6
    Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks

    Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks by Shing, Chiang Ta, Mohammed Al-Andoli, Mohammed Nasser, Wooi, Ping Cheah

    Published 2022
    “…Next, the method is integrated with two optimization algorithms: (1) backpropagation (BP), which optimizes deep learning locally within each local chunk of the CN; (2) particle swarm optimization (PSO), which is used to improve the BP optimization involving all CN chunks. …”
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  7. 7
    A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model

    A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

    Published 2023
    “…Algorithms; Diodes; Errors; Iterative methods; Least squares approximations; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Coefficient of determination; Differential Evolution; Electromagnetism-like algorithm; Hybrid evolutionary algorithm; Photovoltaic; Photovoltaic modules; Root mean square errors; Single-diode models; Evolutionary algorithms; algorithm; comparative study; electromagnetic method; estimation method; experimental design; numerical method; parameterization; performance assessment; photovoltaic system…”
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  8. 8
    A parallel ensemble learning model for fault detection and diagnosis of industrial machinery

    A parallel ensemble learning model for fault detection and diagnosis of industrial machinery by Shing, Chiang Ta, Mohammed Al-Andoli, Mohammed Nasser, Kok, Swee Sim, Seera, Manjeevan, Chee, Peng Lim

    Published 2023
    “…However, the gradient descent optimization method that is commonly used in deep learning suffers from several limitations, such as high computational cost and local sub-optimal solutions. …”
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  9. 9
    PMT: opposition-based learning technique for enhancing meta-heuristic performance

    PMT: opposition-based learning technique for enhancing meta-heuristic performance by Alamri, Hammoudeh S., Kamal Z., Zamli

    Published 2019
    “…Meta-heuristic algorithms have shown promising performance in solving sophisticated real-world optimization problems. …”
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  10. 10
    Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems

    Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems by Mohammad Khamees Khaleel, Alsajri

    Published 2022
    “…To achieve this goal, an improved Teaching Learning-Based Optimization (ITLBO) algorithm was proposed in dealing with subset feature selection. …”
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  11. 11
    MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD

    MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD by MOHAMED OSMAN, MOHAMED ABDELRAHIM

    Published 2017
    “…In this research. novel algorithms have been developed to: (I) isolate the less interacting channe Is using a modified partial correlation algorithm. (2) achieve unbiased and consistent parameter estimates using an iterative LLMS algorithm and (3) develop parsimonious models for closed-loop MIMO systems. …”
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  12. 12
    An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems

    An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems by Muhammad Akmal, Remli, Mohd Saberi, Mohamad, Safaai, Deris, Sinnott, Richard O., Suhaimi, Napis

    Published 2019
    “…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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  13. 13
    Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System

    Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System by Ali, Mohammed Hasan, Mohamed Fadli, Zolkipli

    Published 2019
    “…In this paper, the particle swan optimization algorithm (PSO) was used to obtain an optimal set of initial parameters for Reduce Kernel FLN (RK-FLN), thus, creating an optimal RKFLN classifier named PSO-RKELM. …”
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  14. 14
    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm

    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

    Published 2011
    “…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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  15. 15
    An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems

    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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  16. 16
    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption

    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
    “…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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  17. 17
    ADAPTIVE LINEAR ALGORITHMS FOR POWER SYSTEM FUNDAMENTAL AND HARMONIC ESTIMATION

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

    Published 2015
    “…On the other hand, Least Mean Square (LMS) algorithm is known for its ease of structure, computation and simplicity. …”
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  18. 18
    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems

    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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  19. 19
    Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data

    Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data by Hamza, Abubakar

    Published 2023
    “…The performance of the SA algorithm has been explored in terms of accuracies and estimation errors. …”
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  20. 20
    LASSO-type estimations for threshold autoregressive and heteroscedastic time series models.

    LASSO-type estimations for threshold autoregressive and heteroscedastic time series models. by Muhammad Jaffri Mohd Nasir

    Published 2020
    “…In this thesis, we propose Least Absolute Shrinkage and Selection Operator (LASSO) type estimators to perform simultaneous parameter estimation and model selection for five specific univariate and multivariate time series models, and develop several algorithms to compute these estimators. …”
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