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  1. 1
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
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  2. 2
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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  3. 3
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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  4. 4
    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
    “…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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  5. 5
    Development of a Tuneable Test Problem Generator for Assembly Sequence Planning and Assembly Line Balancing

    Development of a Tuneable Test Problem Generator for Assembly Sequence Planning and Assembly Line Balancing by M. F. F., Ab Rashid, Hutabarat, Windo, Tiwari, Ashutosh

    Published 2012
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  6. 6
    Mining Sequential Patterns Using I-PrefixSpan

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use the efficient data structure for general tree-like framework and separator database to reduce the execution time and memory usage. …”
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  7. 7
    Bats echolocation-inspired algorithms for global optimisation problems

    Bats echolocation-inspired algorithms for global optimisation problems by Nafrizuan, Mat Yahya

    Published 2016
    “…The superior performances of the developed bats echolocation-inspired algorithms are verified through rigorous tests with optimisation benchmark test functions and problems. …”
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  8. 8
    A Modified Bats Echolocation-Based Algorithm for Solving Constrained Optimisation Problems

    A Modified Bats Echolocation-Based Algorithm for Solving Constrained Optimisation Problems by N. M., Yahya, Tokhi, M. O.

    Published 2017
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  9. 9
    Max degree around (MDA) algorithm: a smart and efficient approximate algorithm for Vertex cover and independent set problems

    Max degree around (MDA) algorithm: a smart and efficient approximate algorithm for Vertex cover and independent set problems by Fayaz, Muhammad, Arshad, S, Shah, A.S, Shah, Asadullah

    Published 2016
    “…The proposed algorithm is simple and efficient than the other heuristic algorithms for the MVC problem. …”
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  10. 10
    An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion

    An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion by Haque, Ariful

    Published 2018
    “…The elaborated result of the study will help test engineers to choose the algorithm they need to generate test cases efficiently and optimally.…”
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  11. 11
    Multi-objective spiral dynamic algorithms-based for a better accuracy and diversity

    Multi-objective spiral dynamic algorithms-based for a better accuracy and diversity by Ahmad Azwan, Abdul Razak

    Published 2019
    “…On the other hand, multi-objective algorithm is applicable to solve a problem with two or more objectives. …”
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  12. 12
    Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation

    Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation by M. F. F., Ab Rashid

    Published 2013
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  13. 13
    Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim

    Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim by Che Ibrahim, Mohd Erman Safawie

    Published 2012
    “…This project has the capability to reduce the execution time of application problem using parallel algorithms to increase efficiency of cluster computing. …”
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  14. 14
    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 utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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  15. 15
    Towards Software Product Lines Optimization Using Evolutionary Algorithms

    Towards Software Product Lines Optimization Using Evolutionary Algorithms by Jamil, Muhammad Abid, K Nour, Mohamed, Alhindi, Ahmed Hasan, Awang Abu Bakar, Normi Sham, Arif, Muhammad, Muhammad Aljabri, Tareq

    Published 2019
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  16. 16
    Levy tunicate swarm algorithm for solving numerical and real-world optimization problems

    Levy tunicate swarm algorithm for solving numerical and real-world optimization problems by J. J., Jui, M. A., Ahmad, M. I. M., Rashid

    Published 2022
    “…The proposed Levy Tunicate Swarm Algorithm (LTSA) is a novel metaheuristic algorithm that integrates the Levy distribution into a new metaheuristic algorithm called Tunicate Swarm Algorithm (TSA) to solve numerical and real-world optimization problems. …”
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  17. 17
    Network reconfiguration and control for loss reduction using genetic algorithm

    Network reconfiguration and control for loss reduction using genetic algorithm by Jawad, Mohamed Hassan Izzaldeen

    Published 2010
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  18. 18
    Modified adaptive bats sonar algorithm with doppler effect mechanism for solving single objective unconstrained optimization problems

    Modified adaptive bats sonar algorithm with doppler effect mechanism for solving single objective unconstrained optimization problems by N. A., Azlan, Nafrizuan, Mat Yahya

    Published 2019
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  19. 19
    The Evolutionary Convergent Algorithm: A Guiding Path of Neural Network Advancement

    The Evolutionary Convergent Algorithm: A Guiding Path of Neural Network Advancement by Hosseini E., Al-Ghaili A.M., Kadir D.H., Daneshfar F., Gunasekaran S.S., Deveci M.

    Published 2025
    “…In the past few decades, there have been multiple algorithms proposed for the purpose of solving optimization problems including Machine Learning (ML) applications. …”
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  20. 20
    Modifying maximum likelihood test for solving singularity and outlier problems in high dimensional cases

    Modifying maximum likelihood test for solving singularity and outlier problems in high dimensional cases by Hafeez, Ahmad

    Published 2021
    “…However, the performance of the classical location and scatter estimators is usually flawed by singularity and outliers’ problems in high dimensional data sets. The study aimed to modify the existing ML test by incorporating the Cholesky banded regularization methods and thresholding sample covariance matrix to resolve singularity problems and incorporating the L₁-median with Weiszfeld’s algorithm (MLw) covariance matrix to solve outliers’ problem in high dimensional data sets. …”
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