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  1. 1
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    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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  2. 2
    Automatic Number Plate Recognition on android platform: With some Java code excerpts

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
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  3. 3
    Route Optimization System

    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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    Final Year Project
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  4. 4
    Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Predicting Reservoir Water Level

    Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr... by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

    Published 2024
    “…For water level prediction, lagged rainfall and water level are used. In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”
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  5. 5
    Landslide risk zoning using support vector machine algorithm

    Landslide risk zoning using support vector machine algorithm by Ghiasi V., Pauzi N.I.M., Karimi S., Yousefi M.

    Published 2024
    “…The weighted maps were then combined using the support vector machine algorithm. For the training and testing of the machine, 81 slippery ground points and 81 non-sliding points were used. …”
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  6. 6
    Design and Implementation of Data-at-Rest Encryption for Hadoop

    Design and Implementation of Data-at-Rest Encryption for Hadoop by Wan Nor Shuhadah, Wan Nik, Mohamad Afendee, Mohamed, Zarina, Mohamad, Siti Hanisah, Kamaruzaman

    Published 2017
    “…It is shown that the implementation of AES encryption algorithm is capable to secure data stored in HDFS to some extent.…”
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  7. 7
    Design and Implementation of Data-at-Rest Encryption for Hadoop

    Design and Implementation of Data-at-Rest Encryption for Hadoop by Wan Nor Shuhadah, Wan Nik, Mohamad Afendee, Mohamed, Zarina, Mohamad, Siti Hanisah, Kamaruzaman

    Published 2017
    “…It is shown that the implementation of AES encryption algorithm is capable to secure data stored in HDFS to some extent.…”
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  8. 8
    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly

    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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  9. 9
    Development Of Generative Computer-Aided Process Planning System For Lathe Machining

    Development Of Generative Computer-Aided Process Planning System For Lathe Machining by Zubair, Ahmad Faiz

    Published 2019
    “…Furthermore, to minimize unit production cost, machining parameters including cutting speed (CS), feed rate (f) and depth of cut (d) were optimized for regular form surfaces by using firefly algorithm (FA). …”
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  10. 10
    Optimization machining parameters in pocket milling using genetic algorithm and mastercam

    Optimization machining parameters in pocket milling using genetic algorithm and mastercam by Abdullah, Haslina, Isa, Nurshafinaz, Zakaria, Mohamad Shukri

    Published 2023
    “…Mastercam software has been used to verify the algorithm's results by applying the optimum parameter generated by GA in the Mastercam. …”
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  11. 11
    Support directional shifting vector: A direction based machine learning classifier

    Support directional shifting vector: A direction based machine learning classifier by Kowsher, Md., Hossen, Imran, Tahabilder, Anik, Prottasha, Nusrat Jahan, Habib, Kaiser, Zafril Rizal, M Azmi

    Published 2021
    “…The positional error of the linear function has been modelled as a loss function which is iteratively optimized using the gradient descent algorithm. …”
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  12. 12
    Fuzzy modeling using Bat Algorithm optimization for classification

    Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

    Published 2018
    “…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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    Undergraduates Project Papers
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  13. 13
    Different mutation and crossover set of genetic programming in an automated machine learning

    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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  14. 14
    Different mutation and crossover set of genetic programming in an automated machine learning

    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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  15. 15
    Implementation of RIO in UMJaNetSim / Chan Chin We

    Implementation of RIO in UMJaNetSim / Chan Chin We by Chan, Chin We

    Published 2004
    “…In this project, I will do some research on the recent TCP congestion control and avoidance mechanisms and implement one of the mechanisms into the Java Network Simulator (JaNetSim). …”
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  16. 16
    Predictive modelling of machining parameters of S45C mild steel

    Predictive modelling of machining parameters of S45C mild steel by Abbas, Adnan Jameel

    Published 2016
    “…The PSO1 algorithm which used first main temperature objective function gives the best roughness value (0.52 μm) compared with other algorithms, followed by the AIS2 and PSO2 that give (0.86 μm). …”
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  17. 17
    Extreme learning machine model for state-of-charge estimation of lithium-ion battery using gravitational search algorithm

    Extreme learning machine model for state-of-charge estimation of lithium-ion battery using gravitational search algorithm by Hossain Lipu M.S., Hannan M.A., Hussain A., Saad M.H., Ayob A., Uddin M.N.

    Published 2023
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  18. 18
    Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms

    Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms by Hossain S.K.S., Ali S.S., Rushd S., Ayodele B.V., Cheng C.K.

    Published 2023
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  19. 19
    An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)

    An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

    Published 2024
    “…The scope of this study is tri folded, First, an exhaustive and parametric comparative study on a wide variety of machine learning algorithms is presented to evaluate the performance of machine learning algorithms in energy load prediction. …”
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  20. 20
    A hybrid novel SVM model for predicting CO2 emissions using Multiobjective Seagull Optimization

    A hybrid novel SVM model for predicting CO2 emissions using Multiobjective Seagull Optimization by Ehteram M., Sammen S.S., Panahi F., Sidek L.M.

    Published 2023
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