Search Results - (( initial estimation learning algorithm ) OR ( java implementation learning algorithm ))

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  1. 1

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
    “…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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    Thesis
  2. 2

    Parameter estimation in computational systems biology models: a comparative study of initialization methods in global optimization by Muhammad Akmal, Remli, Nor Syahidatul Nadiah, Ismail, Noor Azida, Sahabudin, Nor Bakiah, Abd Warif

    Published 2022
    “…In this work, several choices of initialization methods are compared and experimental results indicated that the algorithm is sensitive to the initial value of kinetic parameters. …”
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    Article
  3. 3

    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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    Conference or Workshop Item
  4. 4

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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    Thesis
  5. 5

    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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    Thesis
  6. 6

    RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION by CATUR ANDRYANI, NUR AFNY

    Published 2010
    “…The thesis also try to investigate the influence of initialization of RBF weights parameters on the overall learning performance using random method and advanced unsupervised learning, such as clustering techniques, as a comparison. …”
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    Thesis
  7. 7

    Harmony Search-Based Fuzzy Clustering Algorithms For Image Segmentation by Alia, Osama Moh’d Radi

    Published 2011
    “…Fuzzy clustering algorithms, which fall under unsupervised machine learning, are among the most successful methods for image segmentation. …”
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    Thesis
  8. 8

    A comprehensive review of crop yield prediction using machine learning approaches with special emphasis on palm oil yield prediction by Rashid, Mamunur, Bari, Bifta Sama, Yusri, Yusup, Mohamad Anuar, Kamaruddin, Khan, Nuzhat

    Published 2021
    “…Crop yield predictions are carried out to estimate higher crop yield through the use of machine learning algorithms which are one of the challenging issues in the agricultural sector. …”
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    Article
  9. 9
  10. 10

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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    Thesis
  11. 11

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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    Thesis
  12. 12

    Nonstationary signal reconstruction from TVAR coefficients by Najeeb, Athaur Rahman, Gunawan, Teddy Surya, Aibinu, Abiodun Musa

    Published 2018
    “…The proposed method consists of three steps, where in the first step, initial values for TVAR coefficients are estimated from synaptic weights of a three layer Artificial Neural Network (ANN) which is trained using Backpropagation (BP) learning algorithm. …”
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    Proceeding Paper
  13. 13

    Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

    Published 2018
    “…Moreover, the balance between the exploration and exploitation processes in the DPSO framework is considered using a combination of (i) a kernel density estimation technique associated with new bandwidth estimation method and (ii) estimated multi-dimensional gravitational learning coefficients. …”
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    Thesis
  14. 14

    Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition by Ali Yahya, Anwar

    Published 2007
    “…Motivating by these drawbacks, this research proposes a new model of dialogue act recognition in which dynamic Bayesian machine learning is applied to induce dynamic Bayesian networks models from task-oriented dialogue corpus using sets of lexical cues selected automatically by means of new variable length genetic algorithm. …”
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    Thesis
  15. 15

    Machine Learning Based Optimal Design of On-Road Charging Lane for Smart Cities Applications by Shanmugam Y., Narayanamoorthi R., Ramachandaramurthy V.K., Bernat P., Shrestha N., Son J., Williamson S.S.

    Published 2025
    “…The algorithm not only aids in estimating the infrastructure cost of the charging lane but also predicts optimal design parameters using trained data. …”
    Article
  16. 16

    Evaluating Adan vs. Adam: an analysis of optimizer performance in deep learning by Ismail, Amelia Ritahani, Azhary, Muhammad Zulhazmi Rafiqi, Hitam, Nor Azizah

    Published 2025
    “…Choosing a suitable optimization algorithm in deep learning is essential for effective model development as it significantly influences convergence speed, model performance, and the success of the train- ing process. …”
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    Proceeding Paper
  17. 17

    Talkout : Protecting mental health application with a lightweight message encryption by Gavin Teo Juen

    Published 2022
    “…The investigation of lightweight message encryption algorithms is conducted with systematic quantitative literature and experiment implementation in Java and Android running environment. …”
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    Academic Exercise
  18. 18

    Integration of machine learning and remote sensing for above ground biomass estimation through Landsat-9 and field data in temperate forests of the Himalayan region by Anees, Shoaib Ahmad, Mehmood, Kaleem, Khan, Waseem Razzaq, Sajjad, Muhammad, Alahmadi, Tahani Awad, Alharbi, Sulaiman Ali, Luo, Mi

    Published 2024
    “…Through the utilization of openly accessible fine-resolution data and employing the RF algorithm, the research demonstrated promising outcomes in the identification of optimal predictor-algorithm combinations for forest AGB mapping. …”
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    Article
  19. 19

    Feedback error learning control for underactuated acrobat robot with radial basis funtion based FIR filter by Zainul Azlan, Norsinnira, Yamaura, Hiroshi

    Published 2009
    “…Simulation results on a two link acrobat robot with nonzero initial angular momentum in achieving a final desired posture angle are presented to show the validity of the proposed algorithm.…”
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    Proceeding Paper
  20. 20

    An extended adaptive mechanism of evolutionary based channel assignment via reinforcement by Teo, Kenneth Tze Kin, Yew, Hoe Tung, Lye, Scott Carr Ken, Lim, Kit Guan, Ang, Soo Siang, Khairul Anuar Mohamad, Ali Chekima, Liau, Chung Fan, Aroland Jilui Kiring

    Published 2012
    “…The process of channel assignment must satisfy hard-constraints such as electromagnetic compatibility (EMC) and the demand of channels in a cell. Initial channel assignment parameters are obtained using self-learning scheme and evolutionary algorithms is used to fine-tune the estimated parameters from reinforcement learning algorithm to optimise the channel assignment problem in wireless mobile networks. …”
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    Research Report