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  1. 1
    An ensemble learning method for spam email detection system based on metaheuristic algorithms

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…Recently, various techniques based on different algorithms have been developed. However, the classification accuracy and computational cost are not satisfied. …”
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  2. 2
    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
    “…Electing the best set of features will help to improve the classifier predictions in terms of the normal and abnormal pattern. The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. …”
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  3. 3
    Tolerable Constructive Graph-Based Hyper-Heuristic Algorithm For Examination Timetabling

    Tolerable Constructive Graph-Based Hyper-Heuristic Algorithm For Examination Timetabling by Mohammad Pour, Shahrzad

    Published 2009
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  4. 4
    Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems

    Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems by Bashar AbedAl Mohdi Talal AlDeeb

    Published 2024
    “…(iii) It is a constructive-based meta-heuristic algorithm which means, the solution is incrementally constructed (step by step) until the complete solution is obtained (Noferesti and Shah-Hosseini, 2012). …”
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  5. 5
    A constructive approach to examination timetabling based on adaptive decomposition and ordering

    A constructive approach to examination timetabling based on adaptive decomposition and ordering by Abdul Rahman, Syariza, Burke, Edmund K., Bargiela, Andrzej, McCollum, Barry, Özcan, Ender

    Published 2014
    “…In this study, we investigate an adaptive decomposition and ordering strategy that automatically divides examinations into difficult and easy sets for constructing an examination timetable.The examinations in the difficult set are considered to be hard to place and hence are listed before the ones in the easy set in the construction process. …”
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  6. 6
    Hybrid Intelligent Water Drops Algorithm For Examination Timetabling Problem

    Hybrid Intelligent Water Drops Algorithm For Examination Timetabling Problem by Bashar A.Aldeeb, Mohammed Azmi Al-Betar, Norita Md Norwawi, Khalid A.Alissa, Mutasem K.Alsmadi, Ayman A.Hazaymeh, Malek Alzaqebah

    Published 2024
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  7. 7
    Examining performance of aggregation algorithms for neural network-based electricity demand forecasting

    Examining performance of aggregation algorithms for neural network-based electricity demand forecasting by Hassan, S., Khosravi, A., Jaafar, J.

    Published 2015
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  8. 8
    Automated Examination Timetabling System (AETSys) / Ariff Md Ab Malik

    Automated Examination Timetabling System (AETSys) / Ariff Md Ab Malik by Md Ab Malik, Ariff, Haruddin, Hanitahaiza, Alwi, Anisah, Mohamed, Khainizam

    Published 2013
    “…This system has been developed based on a hybridization of local search-population based metaheuristic algorithms. …”
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  9. 9
    Solving Examination Timetabling Problem using Partial Exam Assignment with Great Deluge Algorithm

    Solving Examination Timetabling Problem using Partial Exam Assignment with Great Deluge Algorithm by Ashis Kumar, Mandal, M. N. M., Kahar

    Published 2015
    “…Constructing a quality solution for the examination timetable problem is a difficult task. …”
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  10. 10
    Formulation of macro-micro safety predictors in high-rise construction sites based on dematel algorithm

    Formulation of macro-micro safety predictors in high-rise construction sites based on dematel algorithm by Kang, Chun Xiang

    Published 2024
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  11. 11
    Genetic algorithms for VLSI micro-Cell layout area optimization based on binary tree

    Genetic algorithms for VLSI micro-Cell layout area optimization based on binary tree by Hasliza, A. Rahim@Samsuddin, Ab Al-Hadi, Ab Rahman, R. Badlishah, Ahmad, 'Aini Syuhada, Md Zain, M.I., Ahmad, Wan Nur Suryani Firuz, Wan Arrifin

    Published 2009
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  12. 12
    Imputing incomplete software metric database using iterative nearest neighbour based algorithm

    Imputing incomplete software metric database using iterative nearest neighbour based algorithm by Wasito, Ito, Ab. Azid, Nurul Farihan

    Published 2008
    “…The experiments are carried out using real database for the input of the algorithm for the purpose of relating the missingness data in the real database to examine the accuracy of the imputed data compared to the actual data.…”
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  13. 13
    Dynamic determinant matrix-based block cipher algorithm

    Dynamic determinant matrix-based block cipher algorithm by Juremi, Julia

    Published 2018
    “…This research also proposes a new method namely RotateSwapDeterminant function that uses rotation and swapping of the bit based on the 4x4 determinant computations and will act as the permutation layer in the DDBC algorithm. …”
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  14. 14
    A coalition model for efficient indexing in wireless sensor network with random mobility / Hazem Jihad Ali Badarneh

    A coalition model for efficient indexing in wireless sensor network with random mobility / Hazem Jihad Ali Badarneh by Hazem Jihad , Ali Badarneh

    Published 2021
    “…The second and third scenarios evaluate the performance of Coalition-Based Index-Tree by examining the effects of Dynamic-Coalition framework and Static-Coalition algorithm on Coalition-Based Index-Tree framework. …”
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  15. 15
    Modified artificial neural network (ANN) models for Malaysian construction costs indices (MCCI) data / Saadi Ahmad Kamaruddin

    Modified artificial neural network (ANN) models for Malaysian construction costs indices (MCCI) data / Saadi Ahmad Kamaruddin by Ahmad Kamaruddin, Saadi

    Published 2018
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  16. 16
    Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection

    Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim

    Published 2020
    “…Four state-of-the-art algorithms include particle swarm optimization, flower pollination algorithm, butterfly optimization algorithm, and CBGWO are used to examine the effectiveness of proposed methods in feature selection. …”
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  17. 17
    Optimizing Decentralized Exam Timetabling with a Discrete Whale Optimization Algorithm

    Optimizing Decentralized Exam Timetabling with a Discrete Whale Optimization Algorithm by Emily Siew, Sing Kiang, Sze, San Nah, Goh, Say Leng

    Published 2025
    “…This paper presents a novel discrete Whale Optimization Algorithm approach, integrating the strengths of population-based and local-search algorithms for addressing the examination timetabling problem, a significant challenge many educational institutions face. …”
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  18. 18
    Enhancement of Ant System Algorithm for Course Timetabling Problem

    Enhancement of Ant System Algorithm for Course Timetabling Problem by Djamarus, Djasli

    Published 2009
    “…This research starts with developing an algorithm based on original concept of Ant System Algorithm. …”
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  19. 19
    Artificial Robust Control of Robot Arm: Design a Novel SISO Backstepping Adaptive Lyapunov Based Variable Structure Control.

    Artificial Robust Control of Robot Arm: Design a Novel SISO Backstepping Adaptive Lyapunov Based Variable Structure Control. by Sulaiman, Nasri, Piltan, Farzin, Jalali, Amin, Siamak, Sobhan, Nazari, Iman

    Published 2011
    “…VSC methodology is selected as a framework to construct the control law and address the stability and robustness of the close loop system based on Lyapunove formulation. …”
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  20. 20
    Optimizing decentralized exam timetabling with a discrete whale optimization algorithm

    Optimizing decentralized exam timetabling with a discrete whale optimization algorithm by Emily Sing Kiang Siew, San nah sze, Say leng goh

    Published 2025
    “…This paper presents a novel discrete Whale Optimization Algorithm approach, integrating the strengths of population-based and local-search algorithms for addressing the examination timetabling problem, a significant challenge many educational institutions face. …”
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