Search Results - (( developing smart optimization 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 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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    Thesis
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    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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    Thesis
  3. 3

    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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    Article
  4. 4

    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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    Thesis
  5. 5

    RFID Network Planning of Smart Factory Based on Swarm Intelligent Optimization Algorithm: A Review by YEJIAO, WANG, KAMALUDIN, HAZALILA, MOHAMMED ALDUAIS, NAYEF ABDULWAHAB, MOHD SAFAR, NOOR ZURAIDIN, ZHONGCHAO, HAO

    Published 2024
    “…Therefore, this study reviews smart factories, RFID technology, swarm intelligence optimization algorithms and RFID network planning. …”
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    Article
  6. 6

    Enhanced multi-objective evolutionary mating algorithm with improved crowding distance and levy flight for optimizing comfort index and energy consumption in smart buildings by Muhammad Naim, Nordin, Mohd Herwan, Sulaiman, Nor Farizan, Zakaria, Zuriani, Mustaffa

    Published 2025
    “…This paper introduces a novel Multi-Objective Evolutionary Mating Algorithm (MOEMA) designed to address the inherent challenges of optimizing comfort index and energy consumption in smart building systems. …”
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    Article
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    Intelligent multi-objective control and management for smart energy efficient buildings by Shaikh, P.H., Nor, N.B.M., Nallagownden, P., Elamvazuthi, I., Ibrahim, T.

    Published 2016
    “…The multi-objective genetic algorithm (MOGA) and hybrid multi-objective genetic algorithm (HMOGA) are used as optimization algorithms. …”
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    Article
  9. 9

    Intelligent multi-objective control and management for smart energy efficient buildings by Shaikh, P.H., Nor, N.B.M., Nallagownden, P., Elamvazuthi, I., Ibrahim, T.

    Published 2016
    “…The multi-objective genetic algorithm (MOGA) and hybrid multi-objective genetic algorithm (HMOGA) are used as optimization algorithms. …”
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    Article
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    Smart IoT energy optimisation and localisation monitoring for e-bike sharing by Mohamed, Mawada Ahmed, Toha, Siti Fauziah, Rahman, Md Ataur, Khairudin, Moh.

    Published 2025
    “…The methodology involved integrating sensors to collect key data, implementing connectivity for real-time monitoring, and developing an energy optimization algorithm to prolong battery life, improving the efficiency of the e-bike sharing system. …”
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    Article
  16. 16

    Adaptive rapidly-exploring-random-tree-star (Rrt*) -Smart: algorithm characteristics and behavior analysis in complex environments by Jauwairia Nasir, Fahad Islam, Yasar Ayaz

    Published 2013
    “…Rapidly Exploring Random Trees (RRT) are regarded as one of the most efficient tools for planning feasible paths for mobile robots in complex obstacle cluttered environments. The recent development of its variant: RRT* is considered as a major breakthrough as it makes it possible to achieve optimality in paths planning. …”
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    Article
  17. 17

    Coverage performance analysis of genetic algorithm controlled smart antenna system by Badjian M.M., Thirappa K., Kiong T.S., Paw J.K.S., Krishnan P.S.

    Published 2023
    “…In this paper, an innovative type of smart antenna based on genetic algorithm (GA) has been developed and tested. …”
    Conference paper
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    Stochastic optimized intelligent controller for smart energy efficient buildings by Shaikh, P.H., Nor, N.B.M., Nallagownden, P., Elamvazuthi, I.

    Published 2014
    “…In this study, multi-agent control system has been developed in combination with stochastic optimization using genetic algorithm (GA). …”
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    Comparison of hidden Markov Model and Naïve Bayes algorithms among events in smart home environment by Babakura, Abba, Sulaiman, Md Nasir, Mustapha, Norwati, Kasmiran, Khairul A.

    Published 2014
    “…The subsystems, due to their diversified nature develop difficulties as the events communicate making the smart home uncomfortable. …”
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    Conference or Workshop Item