Search Results - (( java implementation path algorithm ) OR ( pattern learning process 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
    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition

    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. …”
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  6. 6
    Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation

    Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation by Mat Jani H., Lee S.P.

    Published 2023
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    Conference paper
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  7. 7
    Medical Image Analysis Using Deep Learning and Distribution Pattern Matching Algorithm

    Medical Image Analysis Using Deep Learning and Distribution Pattern Matching Algorithm by Jaber M.M., Yussof S., Elameer A.S., Weng L.Y., Abd S.K., Nayyar A.

    Published 2023
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  8. 8
    A Divide-and-Distribute Approach to Single-Cycle Learning HGN Network for Pattern Recognition

    A Divide-and-Distribute Approach to Single-Cycle Learning HGN Network for Pattern Recognition by Muhamad Amin , Anang Hudaya, Khan, Asad I.

    Published 2010
    “…Distributed Hierarchical Graph Neuron (DHGN) is a single-cycle learning distributed pattern recognition algorithm, which reduces the computational complexity of existing pattern recognition algorithms by distributing the recognition process into smaller clusters. …”
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  9. 9
    Financial time series predicting using machine learning algorithms

    Financial time series predicting using machine learning algorithms by Tiong, Leslie Ching Ow *

    Published 2013
    “…Thereafter, Artificial Neural Network (ANN) and Support Vector Machine (SVM) algorithms are implemented separately to train with the trend patterns for predicting the movement direction of financial trends. …”
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  10. 10
    Effect of chaos noise on the learning ability of back propagation algorithm in feed forward neural network

    Effect of chaos noise on the learning ability of back propagation algorithm in feed forward neural network by Azian Azamimi, Uwate, Yoko, Nishio, Yoshifumi

    Published 2010
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  11. 11
    Development of a scaled conjugate gradient algorithm for significant RF neural signal processing

    Development of a scaled conjugate gradient algorithm for significant RF neural signal processing by Mohd Norden, Muhammad Farid Akmal, Mohd Isa, Roshakimah, Mohd Isa, Mohd Roshalizi, S. Abdul Kadir, Ros Shilawani, Md Azli, Muhammad Hariz, Muhammad Akram, Amir Syarif

    Published 2025
    “…Artificial Neural Networks (ANN) are computational models inspired by the human brain, capable of recognizing patterns and making predictions. Scale Conjugate Gradient (SCG) algorithm is an efficient training method for ANN that accelerates the learning process and improves output accuracy. …”
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  12. 12
    An empirical study of pattern leakage impact during data preprocessing on machine learning-based intrusion detection models reliability

    An empirical study of pattern leakage impact during data preprocessing on machine learning-based intrusion detection models reliability by Bouke, Mohamed Aly, Abdullah, Azizol

    Published 2023
    “…In this paper, we investigate the impact of pattern leakage during data preprocessing on the reliability of Machine Learning (ML) based intrusion detection systems (IDS). …”
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  13. 13
    Web usage mining for UUM learning care using association rules

    Web usage mining for UUM learning care using association rules by Ramli, Azizul Azhar

    Published 2004
    “…In order to produce the university E-Learning (UUM Educare) portal usage patterns and user behaviors, this paper implements the high level process of Web usage mining using basic Association Rules algorithm - Apriori Algorithm. …”
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  14. 14
    A New Probabilistic Output Constrained Optimization Extreme Learning Machine

    A New Probabilistic Output Constrained Optimization Extreme Learning Machine by Wong S.Y., Yap K.S., Li X.C.

    Published 2023
    “…Benchmarking; Classification (of information); Constrained optimization; Decision making; Electric power systems; Iterative methods; Knowledge acquisition; Learning algorithms; Pattern recognition; Probability; Confidence threshold; Decision making process; Extreme learning machine; Machine learning approaches; Pattern classification problems; Post-processing procedure; Power system applications; Probabilistic output; Machine learning…”
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  15. 15
    A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification

    A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification by Wong, S.Y., Yap, K.S., Yap, H.J., Tan, S.C.

    Published 2015
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  16. 16
    Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks

    Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks by F. M., Mohammed

    Published 2014
    “…EFMM and EFMM2, are proposed to address a number of limitations in the original FMM learning algorithm. In EFMM, three heuristic rules are introduced to improve the hyperbox expansion, overlap test, and contraction processes. …”
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  17. 17
    Web Usage Mining for UUM Learning Care Using Association Rules

    Web Usage Mining for UUM Learning Care Using Association Rules by Azizul Azhar, Ramli

    Published 2004
    “…In order to produce the university E-Learning (UUM Educare) portal usage patterns and user behaviors, this paper implements the high level process of Web usage mining using basic Association Rules algorithm - Apriori Algorithm. …”
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  18. 18
    IncSPADE: An Incremental Sequential Pattern Mining Algorithm Based on SPADE Property

    IncSPADE: An Incremental Sequential Pattern Mining Algorithm Based on SPADE Property by Omer, Adam, Zailani, Abdullah, Amir, Ngah, Kasypi, Mokhtar, Wan Muhamad Amir, Wan Ahmad, Herawan, Tutut, Noraziah, Ahmad, Mustafa, Mat Deris, Abdul Razak, Hamdan

    Published 2016
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  19. 19
    Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor / Muhammad Nasrul Hakim Adenan

    Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor / Muhammad Nasrul Hakim Adenan by Adenan, Muhammad Nasrul Hakim

    Published 2013
    “…Backpropagation is used as the learning method of ANN model. The algorithm will be developed in MATLAB. …”
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  20. 20
    Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor: article / Muhammad Nasrul Hakim Adenan and Maizatul Zolkapli

    Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor: article / Muhammad Nasrul Hakim Adenan and Maizatul Zolkapli by Hakim Adenan, Muhammad Nasrul, Zolkapli, Maizatul

    Published 2013
    “…Backpropagation is used as the learning method of ANN model. The algorithm will be developed in MATLAB. …”
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