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  1. 1
    Machine Learning-Enabled Communication Approach for the Internet of Medical Things

    Machine Learning-Enabled Communication Approach for the Internet of Medical Things by Rahim Khan, Abdullah Ghani, Samia Allaoua Chelloug, Mohammed Amin, Aamir Saeed, Jason Teo

    Published 2023
    “…For this purpose, the proposed scheme utilises a well-known technique, i.e., Kruskal’s algorithm, to find an optimal path from source to destination wearable devices. …”
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  2. 2
    An improved algorithm in test case generation from UML activity diagram using activity path

    An improved algorithm in test case generation from UML activity diagram using activity path by Hashim, Nor Laily, Salman, Yasir D.

    Published 2011
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  3. 3
    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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  4. 4
    Automated path testing using the negative selection algorithm

    Automated path testing using the negative selection algorithm by Shayma Mustafa Mohi-Aldeen, Radziah Mohamad, Safaai Deris

    Published 2017
    “…Negative selection algorithm (NSA) has been used in this paper to generate test data for path testing automatically. …”
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  5. 5
    Test case generation from state machine with OCL constraints using search-based techniques / Aneesa Ali Ali Saeed

    Test case generation from state machine with OCL constraints using search-based techniques / Aneesa Ali Ali Saeed by Aneesa Ali, Ali Saeed

    Published 2017
    “…A model-driven approach was used for generating abstract test cases from the feasible paths. …”
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  6. 6
    Comparison of path planning in simulated robot

    Comparison of path planning in simulated robot by Ch’ng, Chee Yu’ng

    Published 2020
    “…There are 4 path planning algorithms will be compared, which are Dijkstra’s algorithm, A* algorithm, RapidExploring Random Tree (RRT) algorithm, and the last one is an algorithm modified from A*. …”
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  7. 7
    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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  8. 8
    An efficient virtual tour : a merging of path planning and optimization

    An efficient virtual tour : a merging of path planning and optimization by Abd Latiff, Muhammad Shafie, Hassan, Rohayanti

    Published 2004
    “…Furthermore in a large and complicated virtual environment, users are tending to plan their path and navigate in an automatic manner. This paper describes the result of a research project aimed to integrate a path-planning optimization-algorithm and produce an efficient tour in a virtual environment. …”
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  9. 9
    A Novel Integrating Between Tool Path Optimization Using An ACO Algorithm And Interpreter For Open Architecture CNC System

    A Novel Integrating Between Tool Path Optimization Using An ACO Algorithm And Interpreter For Open Architecture CNC System by Yusof, Yusri, Latif, Kamran, Hatem, Noor, A. Kadir, Aini Zuhra, Mohammed, M.A

    Published 2021
    “…Furthermore, high-performing Ant Colony Optimization (ACO) algorithms were used to optimize the travel path time. …”
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  10. 10
    Development of an automatics parallel parking system for nonholonomic mobile robot

    Development of an automatics parallel parking system for nonholonomic mobile robot by Mohd Fairuz , Abdollah, Syed Najib , Syed Salim, Irma Wani , Jamaludin, Muhammad Nizam , Kamarudin

    Published 2011
    “…A PIC32MX360F512L microcontroller is used in order to generate the algorithm and control the movement of the mobile robot. …”
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  11. 11
    Automatic Test Case Generation from UML Activity Diagram Using Activity Path

    Automatic Test Case Generation from UML Activity Diagram Using Activity Path by Almulham, Yasir Dawood Salman

    Published 2010
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  12. 12
    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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  13. 13
    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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  14. 14
    Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof

    Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

    Published 2019
    “…From the simulation result, by using these sensors information the AUTOWiSARD algorithm can successfully differentiate and classify states without supervision, while the Q-learning algorithm is able to produce and optimized states-actions policy. …”
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  15. 15
    Repetitive mutations in genetic algorithm for software test data generations

    Repetitive mutations in genetic algorithm for software test data generations by Kadhim, Mohammed Majid

    Published 2022
    “…One of the white box testing techniques is path coverage testing. Genetic Algorithm (GA) has proven to be an important method in generating test data for automatic path coverage testing. …”
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  16. 16
    Enhancing simulated kalman filter algorithm using current optimum opposition-based learning

    Enhancing simulated kalman filter algorithm using current optimum opposition-based learning by Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Pebrianti, Dwi, Mohd Falfazli, Mat Jusof, Nor Hidayati, Abdul Aziz, Nor Azlina, Ab. Aziz

    Published 2019
    “…Simulated Kalman filter (SKF) is a new population-based optimization algorithm inspired by estimation capability of Kalman filter. …”
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  17. 17
    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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  18. 18
    Pressure vessel design simulation using hybrid harmony search algorithm

    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
    “…Recently the development of optimization algorithm is rapidly increased. Among several optimization algorithms, Harmony Search (HS) has been recently proposed for solving engineering optimization problems. …”
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  19. 19
    Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots

    Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots by Hanafi Ahmad Hijazi, Patricia Anthony

    Published 2006
    “…Experiments were conducted within a 10% noise environment with different task environment complexities to investigate whether the MOEA is effective for controller synthesis. A simulated Khepera robot is evolved by a Pareto-frontier Differential Evolution (POE) algorithm, and learned through a 3-layer feed-forward artificial neural network, attempting to simultaneously fulfill two conflicting objectives of maximizing robot phototaxis behavior while minimizing the neural network's hidden neurons by generating a Pareto optimal set of controllers. …”
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  20. 20
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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