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  1. 1
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
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  2. 2
    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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  3. 3
    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
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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  4. 4
    Mining Sequential Patterns Using I-PrefixSpan

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

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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  5. 5
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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  6. 6
    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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  7. 7
    A modified genetic algorithm for controller placement problem in SDN distributed network

    A modified genetic algorithm for controller placement problem in SDN distributed network by Ibrahim, Abeer A. Z., Hashim, Fazirulhisyam, Sali, Aduwati, Noordin, Nor K., Fadul, Saber M. E.

    Published 2021
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  8. 8
    Manufacturing process planning optimisation in reconfigurable multiple parts flow lines

    Manufacturing process planning optimisation in reconfigurable multiple parts flow lines by Ismail, Napsiah, Musharavati, Farayi, Hamouda, Abdel Magid Salem, Ramli, Abdul Rahman

    Published 2008
    “…Two modified genetic algorithms are devised and employed to provide the best approximate process planning solution. …”
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  9. 9
    Process Planning Optimization In Reconfigurable Manufacturing Systems

    Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

    Published 2008
    “…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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  10. 10
    Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem

    Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem by Suhazri Amrin, Rahmad, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2022
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  11. 11
    Modified quasi-Newton type methods using gradient flow system for solving unconstrained optimization

    Modified quasi-Newton type methods using gradient flow system for solving unconstrained optimization by Yap, Chui Ying

    Published 2016
    “…We also implement the Newton-type methods on trust region framework by using unit step length to adjust the radius of the region to obtain desired reduction in the objective function. …”
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  12. 12
    Features selection for intrusion detection system using hybridize PSO-SVM

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

    Published 2016
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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  13. 13
    Modelling Autonomous Evacuation Navigation System (AENS) for optimal route using Dijkstra's algorithm

    Modelling Autonomous Evacuation Navigation System (AENS) for optimal route using Dijkstra's algorithm by Abu Samah, Khyrina Airin Fariza

    Published 2016
    “…Through ST adaptation, all subsystems were integrated and using the “Dijkstra’s algorithm” (DA) by modifying its function from shortest path algorithm to safest and shortest algorithm, to the nearest exit. …”
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  14. 14
    Classification of herbs plant diseases via hierachical dynamic artificial neural network after image removal using kernel regression framework

    Classification of herbs plant diseases via hierachical dynamic artificial neural network after image removal using kernel regression framework by Abdullah, Lili Nurliyana, Khalid, Fatimah, Borhan, N.M.

    Published 2011
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  15. 15
    Smart grid: Bio-inspired algorithms energy distributions for data centers

    Smart grid: Bio-inspired algorithms energy distributions for data centers by Woo, Yu Hang

    Published 2025
    “…The system is implemented and simulated using the CloudSim Plus framework under both homogeneous and heterogeneous data centre environments. …”
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  16. 16
    Runtime pluggable CPU scheduler for linux operating system

    Runtime pluggable CPU scheduler for linux operating system by Al-Maweri, Nasr Addin Ahmed Salem

    Published 2010
    “…It added more flexibility to the Linux CPU heduler. It has been implemented in three layers, kernel, modules, and user interface layer, to simplify the framework development and maintenance as well as to maintain performance. …”
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  17. 17
    Review of the grey wolf optimization algorithm: variants and applications

    Review of the grey wolf optimization algorithm: variants and applications by Liu, Yunyun, As’arry, Azizan, Hassan, Mohd Khair, Hairuddin, Abdul Aziz

    Published 2023
    “…The paper begins with a concise introduction to the GWO, providing insight into its natural establishment and conceptual framework for optimization. It then lays out the theoretical foundation and key procedures involved in the GWO, following which it comprehensively examines the most recent iterations of the algorithm and categorizes them into parallel, modified, and hybridized variations. …”
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  18. 18
    Comparative analysis of line search methods in the Steepest Descent algorithm for unconstrained optimization problems / Ahmad Zikri Shukeri, Puteri Qurratu Ain Megat Sulzamzamendi and Suhaida Ibrahim

    Comparative analysis of line search methods in the Steepest Descent algorithm for unconstrained optimization problems / Ahmad Zikri Shukeri, Puteri Qurratu Ain Megat Sulzamzamendi... by Shukeri, Ahmad Zikri, Megat Sulzamzamendi, Puteri Qurratu Ain, Ibrahim, Suhaida

    Published 2024
    “…The study's trajectory takes a subtle turn as it proposes a modified methodology that includes a detailed comparison investigation of several line search strategies inside the SD algorithm. …”
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  19. 19
    Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system

    Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohammad Fadhil, Abas, Bayuaji, Luhur

    Published 2023
    “…Deep neural networks (DNNs) are very dependent on their parameterization and require experts to determine which method to implement and modify the hyper-parameters value. This study proposes an automated-tuned hyper-parameter for DNN using a metaheuristic optimization algorithm, arithmetic optimization algorithm (AOA). …”
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  20. 20
    Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system

    Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system by Ayop Azmi, Nurnajmin Qasrina Ann, Pebrianti, Dwi, Abas, Mohammad Fadhil, Bayuaji, Luhur

    Published 2023
    “…Deep neural networks (DNNs) are very dependent on their parameterization and require experts to determine which method to implement and modify the hyper-parameters value. This study proposes an automated-tuned hyper�parameter for DNN using a metaheuristic optimization algorithm, arithmetic optimization algorithm (AOA). …”
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