Search Results - (( development action method algorithm ) OR ( java implementation path algorithm ))

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  1. 1
    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer

    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer by Ahmad Nezer, Nurul Aqilah

    Published 2017
    “…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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  2. 2
    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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  3. 3
    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment

    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment by Shaliza Hayati A. Wahab, Nordin Saad, Azali Saudi, Ali Chekima

    Published 2021
    “…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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  4. 4
    Smart appointment organizer for mobile application / Mohd Syafiq Adam

    Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

    Published 2009
    “…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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  5. 5
    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 reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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  6. 6
    Development of priority oriented scheduling method to increase the efficiency and reliability for automotive job

    Development of priority oriented scheduling method to increase the efficiency and reliability for automotive job by Nojabaei, Seyedehfarzaneh

    Published 2012
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  7. 7
    Simulation of an adaptive artificial neural network for power system security enhancement including control action

    Simulation of an adaptive artificial neural network for power system security enhancement including control action by Al-Masri, Ahmed Naufal A., Ab Kadir, Mohd Zainal Abidin, Hizam, Hashim, Mariun, Norman

    Published 2015
    “…The developed method is proved to be a steady-state security assessment tool for supplying possible control actions to mitigate an insecure situation resulting from credible contingency. …”
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  8. 8
    Adaptive artificial neural network for power system security assessment and control action

    Adaptive artificial neural network for power system security assessment and control action by Al-Masri, Ahmed Naufal A.

    Published 2012
    “…Finally, a software tool based on an adaptive neural network for power system security assessment was developed. The idea of the AANN approach presented in this thesis is to generalise the security assessment method with the consideration of remedial action for any operating point. …”
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  9. 9
    An interactive analytics approach for sustainable and resilient case studies: a machine learning perspective

    An interactive analytics approach for sustainable and resilient case studies: a machine learning perspective by Mousavi, Seyed Mohsen, Sadeghi R., Kiarash, Lee, Lai Soon

    Published 2023
    “…Sustainable development is a problem-solving method that simultaneously accounts for the economic, environmental, and social impacts of actions. …”
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  10. 10
    The application of suitable sports games for junior high school students based on deep learning and artificial intelligence

    The application of suitable sports games for junior high school students based on deep learning and artificial intelligence by Ji, Xueyan, Samsudin, Shamsulariffin, Hassan, Muhammad Zarif, Farizan, Noor Hamzani, Yuan, Yubin, Chen, Wang

    Published 2025
    “…This study intends to develop a Spatial Temporal-Graph Convolutional Network (ST-GCN) action detection algorithm based on the MediaPipe framework. …”
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  11. 11
    Property premises intruders detection using face recognition method / Joveni Henry

    Property premises intruders detection using face recognition method / Joveni Henry by Joveni Henry

    Published 2017
    “…However, the current action and method that are usually implemented by the owner can be easily violated and not effective. …”
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  12. 12
    Selection, generation and extraction of MCCTree using XMCCTree

    Selection, generation and extraction of MCCTree using XMCCTree by Sazaly, Ummu Sulaim, Selamat, Mohd Hasan, Baharom, Salmi, A. Jabar, Marzanah

    Published 2012
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  13. 13
    Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning

    Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning by Abu Bakar, Mohamad Hafiz, Shamsudin, Abu Ubaidah, Abdul Rahim, Ruzairi, Adil Soomro, Zubair, Adrianshah, Andi

    Published 2023
    “…Through this study, Q-Learning and State-Action-Reward-StateAction (SARSA) are used in this study and the comparison of results involving both the performance and effectiveness of the system based on the simulation of both methods can be seen through the analysis. …”
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  14. 14
    Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning

    Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning by Abu Bakar, Mohamad Hafiz, Shamsudin, Abu Ubaidah, Abdul Rahim, Ruzairi, Zubair Adil Soomro, Zubair Adil Soomro, Andi Adrianshah, Andi Adrianshah

    Published 2023
    “…Through this study, Q-Learning and State-Action-Reward-StateAction (SARSA) are used in this study and the comparison of results involving both the performance and effectiveness of the system based on the simulation of both methods can be seen through the analysis. …”
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  15. 15
    Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning

    Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning by Abu Bakar, Mohamad Hafiz, Shamsudin, Abu Ubaidah, Abdul Rahim, Ruzairi, Soomro, Zubair Adil, Adrianshah, Andi

    Published 2023
    “…Through this study, Q-Learning and State-Action-Reward-StateAction (SARSA) are used in this study and the comparison of results involving both the performance and effectiveness of the system based on the simulation of both methods can be seen through the analysis. …”
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  16. 16
    Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning

    Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning by Abu Bakar, Mohamad Hafiz, Shamsudin, Abu Ubaidah, Abdul Rahim, Ruzairi, Adil Soomro, Zubair, Adrianshah, Andi

    Published 2023
    “…Through this study, Q-Learning and State-Action-Reward-StateAction (SARSA) are used in this study and the comparison of results involving both the performance and effectiveness of the system based on the simulation of both methods can be seen through the analysis. …”
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  17. 17
    Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning

    Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning by Mohamad Hafiz Abu Bakar, Mohamad Hafiz Abu Bakar, Abu Ubaidah Shamsudin, Abu Ubaidah Shamsudin, Ruzairi Abdul Rahim, Ruzairi Abdul Rahim, Zubair Adil Soomro, Zubair Adil Soomro, Andi Adrianshah, Andi Adrianshah

    Published 2023
    “…Through this study, Q-Learning and State-Action-Reward-StateAction (SARSA) are used in this study and the comparison of results involving both the performance and effectiveness of the system based on the simulation of both methods can be seen through the analysis. …”
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  18. 18
    An accurate algorithm of PMU-based wide area measurements for fault detection using positive-sequence voltage and unwrapped dynamic angles

    An accurate algorithm of PMU-based wide area measurements for fault detection using positive-sequence voltage and unwrapped dynamic angles by Muhammad Qasim, Khan, Musse Mohamud, Ahmed, Ahmed Mohamed, Ahmed Haidar

    Published 2022
    “…Among different algorithms, this study focuses on modelling the non- recursive phasor estimation method in a power Simulink environment for a standard test system equipped with a developed algorithm to detect the fault zone. …”
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  19. 19
    A fuzzy approach for early human action detection / Ekta Vats

    A fuzzy approach for early human action detection / Ekta Vats by Ekta, Vats

    Published 2016
    “…Most existing methods deal with the detection of an action after its completion. …”
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  20. 20
    Evolutionary cost-cognizant regression test case prioritization for object-oriented programs

    Evolutionary cost-cognizant regression test case prioritization for object-oriented programs by Bello, AbdulKarim

    Published 2019
    “…Therefore, this study proposed a cost-cognizant TCP approach for object-oriented software that uses path-based integration testing to identify the possible execution path extracted from the Java System Dependence Graph (JSDG) model of the source code using forward slicing technique. …”
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