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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
    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments

    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments by Chiang, A., Baba, M.S.

    Published 2006
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  3. 3
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    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 support vector machines (SVM) algorithm obtained the overall best results of 94.5% accuracy, 91.8% precision, 91.7% recall, and 91.1% f-Measure while the naïve bayes (NB) algorithm obtained the best AUC score of 0.944 with the tweet data of Dato Seri Anwar. …”
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  4. 4
    AI powered asthma prediction towards treatment formulation: an android app approach

    AI powered asthma prediction towards treatment formulation: an android app approach by Murad, Saydul Akbar, Adhikary, Apurba, Md Muzahid, Abu Jafar, Sarker, Md Murad Hossain, Khan, Md. Ashikur Rahman, Hossain, Md. Bipul, Bairagi, Anupam Kumar, Masud, Mehedi, Kowsher, Md

    Published 2022
    “…We collect information on 23 asthma-related characteristics. We utilized eight robust machine learning algorithms to analyze this dataset. …”
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  5. 5
    Object-Oriented Programming semantics representation utilizing agents

    Object-Oriented Programming semantics representation utilizing agents by Mohd Aris, Teh Noranis

    Published 2011
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  6. 6
    AI powered asthma prediction towards treatment formulation : An android app approach

    AI powered asthma prediction towards treatment formulation : An android app approach by Murad, Saydul Akbar, Adhikary, Apurba, Muzahid, Abu Jafar Md, Sarker, Md. Murad Hossain, Khan, Md. Ashikur Rahman, Hossain, Md. Bipul, Bairagi, Anupam Kumar, Masud, Mehedi, Kowsher, Md.

    Published 2022
    “…We collect information on 23 asthma-related characteristics. We utilized eight robust machine learning algorithms to analyze this dataset. …”
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  7. 7
    A block cipher based on genetic algorithm

    A block cipher based on genetic algorithm by Zakaria, Nur Hafiza

    Published 2016
    “…The development of block ciphers have resulted in a number of cryptographic algorithms such as, AES, ARIA, BLOWFISH256, DESL, 3D-AES and many more. …”
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  8. 8
    Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for im Drive

    Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for im Drive by Hannan M.A., Ali J.A., Mohamed A., Amirulddin U.A.U., Tan N.M.L., Uddin M.N.

    Published 2023
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  9. 9
    Computing the autopilot control algorithm using predictive functional control for unstable model

    Computing the autopilot control algorithm using predictive functional control for unstable model by H. A., Kasdirin, J. A., Rossiter

    Published 2009
    “…This paper discusses the computing development of a control algorithm using Predictive Functional Control (PFC) for model-based that having one or more unstable poles. …”
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  10. 10
    Effort Estimation Model for Function Point Measurement

    Effort Estimation Model for Function Point Measurement by Koh, Tieng Wei

    Published 2007
    “…Software Cost Estimation is a practical process that is applied to find out basically the effort and development time requirements for a software product, which is going to be developed. …”
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  11. 11
    Chebyshev approximation of discrete polynomials and splines

    Chebyshev approximation of discrete polynomials and splines by Che Seman, Fauziahanim

    Published 2004
    “…The output of the algorithm is a set of extreme points that can be used to construct a minimal error approximation function. …”
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  12. 12
    Chebyshev approximation of discrete polynomials and splines

    Chebyshev approximation of discrete polynomials and splines by Che Seman, Fauziahanim

    Published 2004
    “…The output of the algorithm is a set of extreme points that can be used to construct a minimal error approximation function. …”
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  13. 13
    A video-rate color image segmentation using adaptive and statistical membership function

    A video-rate color image segmentation using adaptive and statistical membership function by Sojodishijani, Omid, Rostami, Vahid, Ramli, Abdul Rahman

    Published 2010
    “…Typically, the image segmentation algorithms in video processing system require very high computation power, so it is desirable to develop algorithms for implementation as a real-time system. …”
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  14. 14
    A genetic algorithm based approach for economic dispatch in power system / Mohd Rozely Kalil

    A genetic algorithm based approach for economic dispatch in power system / Mohd Rozely Kalil by Kalil, Mohd Rozely

    Published 1998
    “…The Genetic Algorithm developed in the project was tested on two objective functions for optimizing the economic dispatch problem, which are the total generation cost and the incremental cost function. …”
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  15. 15
    A study on regional GDP forecasting analysis based on radial basis function neural network with genetic algorithm (RBFNN-GA) for Shandong economy

    A study on regional GDP forecasting analysis based on radial basis function neural network with genetic algorithm (RBFNN-GA) for Shandong economy by Qing, Zhang, Abdullah, Abdul Rashid, Choo, Wei Chong, Ali, Mass Hareeza

    Published 2022
    “…These basic indicators can comprehensively and effectively reflect a country’s or region’s future economic development. …”
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  16. 16
    Curve Reconstruction By Metaheuristics Algorithms On Cubic Rational Bézier Function

    Curve Reconstruction By Metaheuristics Algorithms On Cubic Rational Bézier Function by Mohamed, Najihah

    Published 2019
    “…The optimisation technique consists of exact algorithm, and approximate algorithm. The approximate algorithm is a good technique to be highlighted since it is a feasible way to develop an easier, more convenient curve fitting method, that will save great computation, solve a large scale problem and produce a better quality end result. …”
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  17. 17
    Development and applications of metaheuristic algorithms in engineering design and structural optimization / Ali Sadollah

    Development and applications of metaheuristic algorithms in engineering design and structural optimization / Ali Sadollah by Ali, Sadollah

    Published 2013
    “…Furthermore, a comparative study was carried out to show the effectiveness of the proposed algorithms over other well-known methods in terms of computational time (speed) and function values. …”
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  18. 18
    Estimation of the denitrification in the lower Mississippi Valley

    Estimation of the denitrification in the lower Mississippi Valley by Saleh, Abdul Razak

    Published 2001
    “…The CREAMS denitrification algorithm is a function of the number of days of drainage from the bottom layer of the profile. …”
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  19. 19
    Designing New Block Cipher Based On Genetic Algorithm Approach

    Designing New Block Cipher Based On Genetic Algorithm Approach by Nur Hafiza Binti Zakaria, Ramlan Mahmod, Nur Izura Udzir, Zuriati Ahmad Zukarnain, Suriyani Ariffin

    Published 2024
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  20. 20
    A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System

    A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System by Wong, Ze-Hao

    Published 2020
    “…Then, the histogram distance function for each location is computed using a pseudo-probability combination of novel histogram distance functions on a clustered histogram. …”
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