Search Results - (( java implementation path algorithm ) OR ( using learning during 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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    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

    Evaluation of optimal MLP structure for heart disease diagnosis / Salbiah Ab Hamid by Ab Hamid, Salbiah

    Published 2010
    “…The weight of each value in hidden layers will be considered during the learning process. LM algorithm is used to minimize the error during training and testing process. …”
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    Thesis
  6. 6

    Early detection of dengue disease using extreme learning machine by Suhaeri, Suhaeri, Mohd Nawi, Nazri, Fathurahman, Muhamad

    Published 2018
    “…The proposed ELM prevents several backpropagation issues by reducing the used of many parameters that solves the main drawbacks of Backpropagation algorithm that uses during the training phase of Neural Network. …”
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    Article
  7. 7

    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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    Thesis
  8. 8

    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. …”
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    Article
  9. 9

    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…There are two general paradigms for pattern recognition classification which are supervised and unsupervised learning. The problems in applying unsupervised learning/clustering is that this method requires teacher during the classification process and it has to learn independently which may lead to poor classification. …”
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    Thesis
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    Improved rsync algorithm to minimize communication cost using multi-agent systems for synchronization in multi-learning management systems by Mwinyi, Amir Kombo

    Published 2017
    “…Therefore, the aim of this study is to minimize the computation time during RFS by improving the standard rsync algorithm. …”
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    Thesis
  12. 12

    Evaluation of rehearsal effects of multimedia content based on EEG using machine learning algorithms by Mazher, M., Aziz, A.A., Malik, A.S.

    Published 2017
    “…Three frequency based features are used to discriminate the three learning states mentioned as L1, L2 and L3 using machine learning algorithms. …”
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    Article
  13. 13

    Fast sequential learning methods on RBF-network using decomposed training algorithms by Asirvadam , Vijanth Sagayan, McLoone, Sean, Irwin, George W

    Published 2004
    “…This work investigates novel sequential learning methods applied on a decomposed form of training algorithms using radial basis function (RBF) network. …”
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    Conference or Workshop Item
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    Mobile machine vision for railway surveillance system using deep learning algorithm by Kit, Guan Lim, Daniel Siruno, Min, Keng Tan, Chung, Fan Liau, Sha, Huang, Tze, Kenneth Kin Teo

    Published 2021
    “…This model can be implemented with Raspberry Pi to simulate the object detection algorithm virtually. During simulation, the object recognition algorithm is able to detect and classify various objects into its respective classes. …”
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    Proceedings
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    Artificial intelligent integrated into sun-tracking system to enhance the accuracy, reliability and long-term performance in solar energy harnessing by Tan, Jun You

    Published 2022
    “…The proposed AI algorithm integrates two deep learning models which are object detection algorithm and reinforcement learning. …”
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    Final Year Project / Dissertation / Thesis
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    Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

    Published 2021
    “…Optimization algorithms are widely used for the identification of intrusion. …”
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    Article
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    Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

    Published 2014
    “…Bat algorithm is an optimizer tool and developed using of echolocation characteristics of bats, while the neural network is learning methods that approach the human brain using artificial neurons. …”
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    Article
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