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  1. 1
    Opposition- based simulated kalman filters and their application in system identification

    Opposition- based simulated kalman filters and their application in system identification by Kamil Zakwan, Mohd Azmi

    Published 2017
    “…Among the various kinds of optimization algorithms, Simulated Kalman Filter (SKF) is a new population-based optimization algorithm inspired by the estimation capability of Kalman Filter. …”
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  2. 2
    Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization

    Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization by Yap, David F. W., Koh, S. P., Tiong, S. K.

    Published 2011
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  3. 3
    BAT-BP: A new BAT based back-propagation algorithm for efficient data classification

    BAT-BP: A new BAT based back-propagation algorithm for efficient data classification by Mohd. Nawi, Nazri, M. Z., Rehman, Hafifi, Nurfarian, Khan, Abdullah, Siming, Insaf Ali

    Published 2016
    “…Training neural networks particularly back propagation algorithm is a complex task of great importance in the field of supervised learning. …”
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  4. 4
    Improved opposition-based particle swarm optimization algorithm for global optimization

    Improved opposition-based particle swarm optimization algorithm for global optimization by Nafees Ul Hassan, Waqas Haider Bangyal, M. Sadiq Ali Khan, Kashif Nisar, Ag. Asri Ag. Ibrahim, Danda B. Rawat

    Published 2021
    “…Particle Swarm Optimization (PSO) has been widely used to solve various types of optimization problems. …”
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  5. 5
    Unsupervised Deep Learning Algorithm to Solve Sub-Surface Dynamics for Petroleum Engineering Applications

    Unsupervised Deep Learning Algorithm to Solve Sub-Surface Dynamics for Petroleum Engineering Applications by Kumar, A., Ridha, S., Ilyas, S.U.

    Published 2020
    “…In the present study, the solution for the initial condition and boundary value problems in ordinary and partial differential equation by deep learning method have been analyzed. The propsed algorithm could be valuable aid for analyzing the fluid flow and reservoir simulation in an effective manner. …”
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  6. 6
    Nomadic people optimizer (NPO) for large-scale optimization problems

    Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

    Published 2019
    “…The final problem is the ability of the algorithm to solve large-scale problems, which mostly are the real world problems. …”
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  7. 7
    Optimizing dam and reservoir operations using machine learning

    Optimizing dam and reservoir operations using machine learning by Mohammad Abdullah Adib Almubaidin

    Published 2025
    text::Thesis
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  8. 8
    Deep Reinforcement Learning For Control

    Deep Reinforcement Learning For Control by Bakar, Nurul Asyikin Abu

    Published 2021
    “…In essence, the method is to use a reward-based learning environment to watch how the agent makes decisions. …”
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  9. 9
    Deep reinforcement learning online offloading for SWIPT multiple access edge computing network

    Deep reinforcement learning online offloading for SWIPT multiple access edge computing network by Teckchai, Tiong, Ismail Saad, Tze, Kenneth Kin Teo, Herwansyah Lago

    Published 2021
    “…Simulation results are presented to demonstrate that the proposed algorithm is able to approach near-optimal performance and superior in decreasing tasks computation time compared with existing optimization methods, enabling real time optimal resource allocation and offloading achievable in a fast-fading wireless environment.…”
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  10. 10
    A new modern scheme for solving fractal–fractional differential equations based on deep feedforward neural network with multiple hidden layer

    A new modern scheme for solving fractal–fractional differential equations based on deep feedforward neural network with multiple hidden layer by Admon, Mohd Rashid, Senu, Norazak, Ahmadian, Ali, Majid, Zanariah Abdul, Salahshour, Soheil

    Published 2024
    “…During the initial stage of the method development, the basic framework on solving FFDEs is designed. …”
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  11. 11
    Simultaneous computation of model order and parameter estimation for system identification based on opposition-based simulated Kalman filter

    Simultaneous computation of model order and parameter estimation for system identification based on opposition-based simulated Kalman filter by Badaruddin, Muhammad, Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Ahmad Afif, Mohd Faudzi, Pebrianti, Dwi

    Published 2018
    “…However, the performance was worse than conventional ARX method. Current optimum opposition-based simulated Kalman filter (COOBSKF) is an improved version of simulated Kalman filter (SKF) which employs the concept of current optimum opposition-based learning (COOBL). …”
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  12. 12
    Studying the Impact of Initialization for Population-Based Algorithms with Low-Discrepancy Sequences

    Studying the Impact of Initialization for Population-Based Algorithms with Low-Discrepancy Sequences by Adnan Ashraf, Sobia Pervaiz, Waqas Haider Bangyal, Kashif Nisar, Ag. Asri Ag. Ibrahim, Joel J. P. C. Rodrigues, Danda B. Rawat

    Published 2021
    “…To solve different kinds of optimization challenges, meta-heuristic algorithms have been extensively used. …”
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  13. 13
    Maximizing deep learning-based energy efficiency in 5G downlink MIMO-NOMA systems by using MLP-CNN.

    Maximizing deep learning-based energy efficiency in 5G downlink MIMO-NOMA systems by using MLP-CNN. by Audah, Kamil, Hussein, Walaa, Noordin, Nor Kamariah, Sali, Aduwati, A.Rasid, Mohd Fadlee

    Published 2024
    “…It can be utilized with multiple convolutional and hidden layers, trained using specific algorithms to solve power allocation problems. Simulation results demonstrate that the proposed framework improves power allocation, overall data rates, and Energy efficiency by around 15% compared to traditional deep neural network (DNN) algorithms, methods and strategies.…”
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  14. 14
    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
    “…Then, this study aims to optimize the hyperparameters of the developed DNN model using the Arithmetic Optimization Algorithm (AOA) and, lastly, to evaluate the performance of the newly proposed deep learning model with Simulated Kalman Filter (SKF) algorithm in solving image encryption application. …”
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  15. 15
    Nature-Inspired cognitive evolution to play Ms. Pac-Man

    Nature-Inspired cognitive evolution to play Ms. Pac-Man by Tse, Guan Tan, Jason Teo, Patricia Anthony

    Published 2011
    “…The focus of this research is to explore the hybridization of nature-inspired computation methods for optimization of neural network-based cognition in video games, in this case the combination of a neural network with an evolutionary algorithm. …”
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  16. 16
    CFD modeling on coal properties towards the burnout efficiency

    CFD modeling on coal properties towards the burnout efficiency by Nabil Asyraf Abd Halim

    Published 2024
    text::Final Year Project
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  17. 17
    Opposition-based learning simulated kalman filter for Numerical optimization problems

    Opposition-based learning simulated kalman filter for Numerical optimization problems by Mohd Falfazli, Mat Jusof

    Published 2016
    “…Simulated Kalman Filter (SKF) optimization algorithm is a population-based optimizer operated mainly based on Kalman filtering. …”
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  18. 18
    Investigating the Performance of Deep Reinforcement Learning-Based MPPT Algorithm under Partial Shading Condition

    Investigating the Performance of Deep Reinforcement Learning-Based MPPT Algorithm under Partial Shading Condition by Yew W.H., Fat Chau C., Mahmood Zuhdi A.W., Syakirah Wan Abdullah W., Yew W.K., Amin N.

    Published 2024
    “…These DRL-based algorithms optimize the local and global maximum power point (MPP) using deep Q-learning and deep deterministic policy gradient (DDPG). …”
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  19. 19
    Deriving Optimal Operation Rule for Reservoir System Using Enhanced Optimization Algorithms

    Deriving Optimal Operation Rule for Reservoir System Using Enhanced Optimization Algorithms by Almubaidin M.A., Ahmed A.N., Sidek L.M., AL-Assifeh K.A.H., El-Shafie A.

    Published 2025
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  20. 20
    A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules

    A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules by Rizauddin, Saian

    Published 2013
    “…In the first proposed algorithm, SA is used to optimize the rule's discovery activity by an ant. …”
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