Search Results - (( using simulation learning algorithm ) OR ( based simulation based algorithm ))

Refine Results
  1. 1
  2. 2

    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. …”
    Get full text
    Get full text
    Research Book Profile
  3. 3

    Autonomous path planning robot using geographical information by Ismail Ishaq Ibrahim

    Published 2008
    “…The performance of the guidance algorithm will be compared with an existing guidance algorithm based on kinematics geometry and with an alternative guidance strategy employing geometrical analysis and Matlab’s simulation. …”
    Get full text
    Learning Object
  4. 4
  5. 5

    Adaptive beamforming algorithm based on Simulated Kalman Filter by Kelvin Lazarus, Lazarus

    Published 2017
    “…Zakwan, applies Opposition-Based Learning method to improve the exploration capabilities of SKF algorithm. …”
    Get full text
    Get full text
    Thesis
  6. 6

    Octane number prediction for gasoline blends using convolution neural network / Zhu Yue by Zhu , Yue

    Published 2021
    “…In the project three commonly use algorithm are used for prediction of octane number for gasoline blends, which describes the behavior of the fuel in the engine at lower temperatures and speeds, and is an attemp to simulate acceleration behavior.These tree algorithm are back propagation (BP), radial basis funtion (RBF) and Extreme learning machine (ELM) algorithm. …”
    Get full text
    Get full text
    Get full text
    Thesis
  7. 7

    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. …”
    Get full text
    Get full text
    Thesis
  8. 8

    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). …”
    Conference Paper
  9. 9

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

    Published 2013
    “…The simulation was conducted using MATLAB/Simulink software package whilstthe experimental study utilized the existing experimental rig with a hardware-in-the-loop simulation (HILS) configuration with the proposed ILC algorithms incorporated as the new research contribution. …”
    Get full text
    Get full text
    Thesis
  10. 10

    E4ML: Educational Tool for Machine Learning by Sainin, Mohd Shamrie, Siraj, Fadzilah

    Published 2003
    “…There are various types of machine learning algorithms with certain processes taken by the algorithm.In teaching of the machine learning algorithms, such processes need to be explained especially to the beginner in introductory level.This paper discusses the development the tool that addresses the process by certain algorithm to produce a hypothesis or output based on given data.This tool can also be used in teaching and learning purposes.The explanation of processes by the algorithms is demonstrated through simple simulation.The source of the algorithms was adapted from Mitchell book [1] that cover popular algorithms in machine learning for teaching and learning such as Concept Learning, Decision Tree, Bayesian Learning, Neural Networks, and Instance based Learning.The tool also used several classes of Weka (Waikato Environment for Knowledge Analysis) as a basis for the design and implementation of the new tool that focuses on explaining the processes taken by certain algorithm.…”
    Get full text
    Get full text
    Conference or Workshop Item
  11. 11

    A comparative study and simulation of object tracking algorithms by Ji, Yuanfa, Yin, Pan, Sun, Xiyan, Kamarul Hawari, Ghazali, Guo, Ning

    Published 2020
    “…This article introduces the popular object tracking algorithms, from common problems in object tracking to the classification of algorithms: Early classic trackingalgorithms, tracking algorithms based on kernel correlation filtering, and tracking algorithms based on deep learning. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  12. 12

    A harmony search-based learning algorithm for epileptic seizure prediction by Kee, Huong Lai, Zainuddin, Zarita, Ong, Pauline

    Published 2016
    “…The proposed harmony search-based learning algorithm is used in the task of epileptic seizure prediction. …”
    Get full text
    Get full text
    Article
  13. 13

    Pressure vessel design simulation using hybrid harmony search algorithm by Alaa A., Alomoush, Mohammed I., Younis, Khalid S., Aloufi, Alsewari, Abdulrahman A., Kamal Z., Zamli

    Published 2019
    “…The hybrid algorithms consist of well-known variants of HS and an opposition-based learning technique. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  14. 14

    A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network by Mohammad Azmi Ridwan, Dr.

    Published 2023
    “…The dataset development for both algorithms is carried out via simulations in Graphical Network Simulator 3 (GNS3). …”
    text::Thesis
  15. 15

    An oppositional learning prediction operator for simulated kalman filter by Zuwairie, Ibrahim, Kamil Zakwan, Mohd Azmi, Badaruddin, Muhammad, Mohd Falfazli, Mat Jusof, Nor Azlina, Alias, Nor Hidayati, Abdul Aziz, Mohd Ibrahim, Shapiai

    Published 2018
    “…The proposed prediction operator is based on oppositional learning. The results show that using CEC2014 as benchmark problems, the SKF algorithm with oppositional learning prediction operator outperforms the original SKF algorithm in most cases.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  16. 16

    Fog-cloud scheduling simulator for reinforcement learning algorithms by Al-Hashimi, Mustafa Ahmed Adnan, Rahiman, Amir Rizaan, Muhammed, Abdullah, Hamid, Nor Asilah Wati

    Published 2023
    “…This study presents a developed simulator that captures all mentioned realistic scenarios by providing the feature of integrability with the reinforcement learning (RL) algorithm. …”
    Get full text
    Get full text
    Article
  17. 17

    Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

    Published 2025
    “…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. …”
    Article
  18. 18

    Implementation of hashed cryptography algorithm based on cryptography message syntax by Ali, Mohammed Ahnaf

    Published 2019
    “…The problematic message uses light blue representation in simulation. The sent message uses the red color representation in the simulation. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  19. 19
  20. 20

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

    Published 2019
    “…The proposed handover algorithms are validated using the LTE-Sim simulator under an urban environment. …”
    Get full text
    Get full text
    Thesis