Search Results - (( java implementation learning algorithm ) OR ( program model machine 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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    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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    Article
  4. 4

    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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  5. 5

    Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed co-gasification of biomass wastes from oil palm by Ayodele B.V., Mustapa S.I., Kanthasamy R., Mohammad N., AlTurki A., Babu T.S.

    Published 2023
    “…Biomass; Catalysis; Digital storage; Gasification; Gaussian distribution; Hydrogen production; Learning algorithms; Lime; Palm oil; Quadratic programming; Regression analysis; Sensitivity analysis; Synthesis gas; Co-gasification; Gaussian process regression; Hydrogen-rich syngas; Machine learning algorithms; Non-linear response; Performance; Quadratic modeling; Renewable energies; Support vectors machine; Syn gas; Support vector machines…”
    Article
  6. 6

    Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat by Fatima, Jannat

    Published 2022
    “…There is also growing interest in modeling machine learning and deep learning algorithms that can learn from user’s data, understand and react to that individual’s affective state. …”
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  7. 7

    Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed co-gasification of biomass wastes from oil palm by Ayodele, B.V., Mustapa, S.I., Kanthasamy, R., Mohammad, N., AlTurki, A., Babu, T.S.

    Published 2022
    “…Taking advantage of the data generated from the process, this study explores the performance of twelve machine learning algorithms built on the support vector machine (SVM), the Gaussian process regression (GPR), and the non-linear response quadratic model (NLRQM) using Sequential quadratic programming, and the Levenberg-Marquardt algorithms. …”
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    Article
  8. 8

    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

    Published 2004
    “…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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  9. 9

    Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed co-gasification of biomass wastes from oil palm by Ayodele, B.V., Mustapa, S.I., Kanthasamy, R., Mohammad, N., AlTurki, A., Babu, T.S.

    Published 2022
    “…Taking advantage of the data generated from the process, this study explores the performance of twelve machine learning algorithms built on the support vector machine (SVM), the Gaussian process regression (GPR), and the non-linear response quadratic model (NLRQM) using Sequential quadratic programming, and the Levenberg-Marquardt algorithms. …”
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    Article
  10. 10

    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
  11. 11

    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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    A new domain specific scripting language for automated machine learning pipeline by Masrom, S., Rahman, A.S.A., Omar, N., Baharun, N.

    Published 2019
    “…From the varieties of the machine learning algorithms, selecting the best model with the best configurations is a critical and complex design issue. …”
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  14. 14

    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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    Rapid software framework for the implementation of machine learning classification models by Rahman, A.S.A., Masrom, S., Rahman, R.A., Ibrahim, R.

    Published 2021
    “…Additionally, this paper explains comparisons of results between two platforms of rapid software; the proposed software and Python program. The machine learning model in the two platforms were tested on breast cancer and tax avoidance datasets with Decision Tree algorithm. …”
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    Article
  16. 16

    Genetic programming based machine learning in classifying public-private partnerships investor intention / Ahmad Amin ... [et al.] by Amin, Ahmad, Rahmawaty, Rahmawaty, Lautania, Maya Febrianty, Abdul Rahman, Rahayu

    Published 2023
    “…The PPP data was analyzed in this study using two machine learning approaches, Genetic Programming and conventional machine learning, with testing results showing that all machine learning algorithms from both approaches achieved high accuracy rates of over 80%, with the Genetic Programming machine learning outperformed the conventional approach. …”
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    Article
  17. 17

    Scheduling dynamic cellular manufacturing systems in the presence of cost uncertainty using heuristic method by Delgoshaei, Aidin

    Published 2016
    “…In this regard, 4 mathematical programming models are developed for forming cells and scheduling the materials on appropriate machines while the system costs are considered uncertain. …”
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  18. 18

    Development of dynamic programming algorithm for maintenance scheduling problem by Zafira Adlia, Mohd Fauzi

    Published 2020
    “…Using the dynamic programming algorithm developed, the model was also able to recalculate alternative schedules by replacing unavailable teams with other teams to avoid delays. …”
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  19. 19

    Machine learning predictions of stock market pattern using Econophysics approach by Roslan, Nur Nadia Hani, Abdullah, Shahino Mah

    Published 2025
    “…There are various techniques for identifying and observing the stock market patterns, one of the techniques is to use Python programming to evaluate and possibly forecast stock market behaviour through predictive modelling, combining both machine learning and Econophysics insights. …”
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    Book Section
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    Implementation of PID controller on prasmatic control of universal stretch and bending machine (USBM) simplified model by Mohd Afiq, Mat Noor

    Published 2008
    “…In this project, generally the project is about implementation of PID controller on prasmatic control of universal stretch and bending machine (USBM) simplified model. The focus on this project is to use a controller as the control algorithm to control the position and movement of servo pneumatic valve. …”
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    Undergraduates Project Papers