Search Results - (( java implementation path algorithm ) OR ( problem representation learning 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
  2. 2

    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 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

    Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms by Koh, Johnny Siaw Paw

    Published 2008
    “…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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    Thesis
  6. 6

    Object-Oriented Programming semantics representation utilizing agents by Mohd Aris, Teh Noranis

    Published 2011
    “…It is very important to handle this problem from the beginning before novices learn more advanced OOP concepts like encapsulation, inheritance, and polymorphism. …”
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    Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering by He, Yanfang

    Published 2024
    “…Although the swmcan algorithm solves the noise problem in multi-view data, its initial and final graphs are independent and cannot learn from each other. …”
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  9. 9

    Problem Solving by Yahaya, Azizi

    Published 2010
    “…Building on the previous work of yourself and others. Transfer of learning and viewing each problem as a learning opportunity. …”
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    Article
  10. 10

    The influence of students’ concept of mole, problem representation ability and mathematical ability on stoichiometry problem solving by Taha, Hafsah, Hashim, Rosnani, Ismail, Zurida, Jusoff, Kamaruzaman, Khoo, Yin Yin

    Published 2014
    “…Students ought to be exposed and guided to understand the underlying conceptual foundation of stoichiometry before introducing the algorithmic way of solving the problems. Keywords: stoichiometry problem solving; mole concept; problem representation ability; mathematical ability…”
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  11. 11

    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

    Published 2006
    “…Traditional schema theory does not support Lamatckian learning, i.e, forcing the genetic representation to match the solution found by the learning algorithm. …”
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  12. 12

    Learning representations of network traffic using deep neural networks for network anomaly detection: A perspective towards oil and gas it infrastructures by Naseer, S., Ali, R.F., Dominic, P.D.D., Saleem, Y.

    Published 2020
    “…A total of sixty anomaly detectors were trained by authors using twelve conventional Machine Learning algorithms to compare the performance of aforementioned deep representations with that of a human-engineered handcrafted network data representation. …”
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    Article
  13. 13

    Hybrid Ant Colony Optimization For Two Satisfiability Programming In Hopfield Neural Network by Kho, Liew Ching

    Published 2019
    “…The representation of 2 Satisfiability problem or 2SAT is increasingly viewed as a significant logical rule in order to synthesize many real life applications. …”
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  14. 14

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

    Published 2019
    “…Hence, the fragmented CMS encryption algorithm will solve this problem and the errors in the message will be removed. …”
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    Visualization Tool for Pathfinding Algorithms by Mathias Sam, Francis

    Published 2023
    “…By incorporating interactive features and step-by-step animations of popular pathfinding algorithms, the tool empowers students to actively engage in the learning process and experiment with different algorithmic approaches. …”
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    Final Year Project Report / IMRAD
  17. 17

    Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches by Al Mahmud, Suaib, Kamarulariffin, Abdurrahman, Mohd Ibrahim, Azhar, Haja Mohideen, Ahmad Jazlan

    Published 2024
    “…In this review paper, a comprehensive review of mobile robot navigation algorithms has been conducted. The findings suggest that, even though the self-learning algorithms require huge amounts of training data and have the possibility of learning erroneous behavior, they possess huge potential to overcome challenges rarely addressed by the other traditional algorithms. …”
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  18. 18

    Extremal region detection and selection with fuzzy encoding for food recognition by Razali @ Ghazali, Mohd Norhisham

    Published 2019
    “…Three algorithms were used to accomplish the task of feature representation. …”
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    Thesis
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    Localized deep extreme learning machines for efficient RGB-D object recognition by Mohd Zaki, Hasan Firdaus, Shafait, Faisal, Mian, Ajmal S.

    Published 2015
    “…Existing RGB-D object recognition methods either use channel specific handcrafted features, or learn features with deep networks. The former lack representation ability while the latter require large amounts of training data and learning time. …”
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    Proceeding Paper