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  1. 1
    Open access for gamification: a systematic review of literature across disciplines

    Open access for gamification: a systematic review of literature across disciplines by Zakaria, Noor Syamilah, Saripan, M. Iqbal, Subarimaniam, Neerushah, Ismail, Alyani

    Published 2020
    “…We found that gamification fits numerous purposes and fields, allowing developers to expand their algorithms to be used for various subjects in different settings. …”
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  2. 2
    Self learning module on securing IPV6 deployment / Muhamad Nazif Shahaimi Zaha

    Self learning module on securing IPV6 deployment / Muhamad Nazif Shahaimi Zaha by Zaha, Muhamad Nazif Shahaimi

    Published 2019
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  3. 3
    Gamification of Regional Tourism Engagement: Analysis and Design of a Web-Based Information System

    Gamification of Regional Tourism Engagement: Analysis and Design of a Web-Based Information System by Johannes Hamonangan, Siregar, Rufman Iman, Akbar, Augury, El Rayeb, Chaerul, Anwar, Suriati Khartini, Jali, Mohamad Imran, Bandan, Phei Chin, Lim, Abby Lian, Hendrick

    Published 2025
    “…The system integrates a structured gamification algorithm with a scalable relational database model, built using React.js and Firebase, to ensure responsive and consistent user experiences. …”
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  4. 4
    VHDL modeling of optimum measurement selection by using genetic algorithm

    VHDL modeling of optimum measurement selection by using genetic algorithm by Ullah, Mohammad Habib, Hasan, Muhammad Asfarul, Uddin, Md. Jasim, Priantoro, Akhmad Unggul

    Published 2009
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  5. 5
    A hybrid particle swarm optimization approach and its application to solving portfolio selection problems

    A hybrid particle swarm optimization approach and its application to solving portfolio selection problems by Shamshul Bahar, Yaakob, Prof. Madya, Watada, Junzo

    Published 2011
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  6. 6
    An ensemble feature selection method to detect web spam

    An ensemble feature selection method to detect web spam by Oskouei, Mahdieh Danandeh, Razavi, Seyed Naser

    Published 2018
    “…In addition, it improves classification metrics in comparison to basic feature selection methods.…”
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  7. 7
    Enhanced Distributed Learning Classifier System For Simulated Mobile Robot Behaviours

    Enhanced Distributed Learning Classifier System For Simulated Mobile Robot Behaviours by Baneamoon, Saeed Mohammed Saeed

    Published 2010
    “…This thesis proposes methods that can overcome the problems of good behaviour selection and good behaviour deletion. …”
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  8. 8
    Development Of Double Stage Filter (DSF) On Stereo Matching Algorithm For 3D Computer Vision Applications

    Development Of Double Stage Filter (DSF) On Stereo Matching Algorithm For 3D Computer Vision Applications by Teo, Chee Huat

    Published 2016
    “…Based on the results of evaluations, the results obtained by DSF is better than the algorithms, basic block matching and dynamic programming.…”
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  9. 9
    Improved Multi-Verse Optimizer In Text Document Clustering For Topic Extraction

    Improved Multi-Verse Optimizer In Text Document Clustering For Topic Extraction by Abasi, Ammar Kamal Mousa

    Published 2021
    “…To achieve this aim: First, A new feature selection method for TDC, that is, binary multi-verse optimizer algorithm (BMVO) is proposed to eliminate irrelevantly, redundant features and obtain a new subset of more informative features. …”
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  10. 10
    Designing machine learning frameworks for intelligence and gamification research / Nordin Abu Bakar

    Designing machine learning frameworks for intelligence and gamification research / Nordin Abu Bakar by Abu Bakar, Nordin

    Published 2016
    “…The central part of this subject is described in terms of frameworks or algorithms that explains how to achieve better performance. …”
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  11. 11
    Master-leader-slave cuckoo search with parameter control for ANN optimization and its real-world application to water quality prediction

    Master-leader-slave cuckoo search with parameter control for ANN optimization and its real-world application to water quality prediction by Jaddi N.S., Abdullah S., Malek M.A.

    Published 2023
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  12. 12
    Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus

    Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus by Darus, Zamzuhairi

    Published 2003
    “…A systematic method for selecting the ANN's input variables was developed using Matlab Programming language.…”
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  13. 13
    Flowshop scheduling using artificial bee colony (ABC) algorithm with varying onlooker bees approaches

    Flowshop scheduling using artificial bee colony (ABC) algorithm with varying onlooker bees approaches by Mohd Pauzi, Nur Fazlinda

    Published 2015
    “…Artificial Bee Colony (ABC) algorithm is one of the methods used to solve the flowshop scheduling problem but only a few researches have been found using this method in this area. …”
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  14. 14
    Robust correlation feature selection based support vector machine approach for high dimensional datasets

    Robust correlation feature selection based support vector machine approach for high dimensional datasets by Baba, Ishaq Abdullahi, Mohammed, Mohammed Bappah, Jillahi, Kamal Bakari, Umar, Aliyu, Hendi, Hasan Talib

    Published 2025
    “…Correlation-based feature selection methods are popular tools used to select the most important variables to include the true model in the analysis of sparse and high-dimensional models. …”
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  15. 15
    Static image of hand gesture for numerical sign language recognition system using backfrofagation neural network / Erman Ibrahim

    Static image of hand gesture for numerical sign language recognition system using backfrofagation neural network / Erman Ibrahim by Ibrahim, Erman

    Published 2007
    “…Finally, the BP algorithm has been prove as a method that can be used for recognizing hand gesture for sign language and the successful task of recognition also dependent an the hnage processing. …”
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  16. 16
    A phonetically rich and balanced lexical corpus using zipfian distribution for an under resourced language / Aminath Farshana

    A phonetically rich and balanced lexical corpus using zipfian distribution for an under resourced language / Aminath Farshana by Aminath , Farshana

    Published 2018
    “…The performance of the proposed method was also evaluated by comparing the results with an existing benchmark method (greedy algorithm). …”
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  17. 17
    Shapeable Maximum-Power Point-Tracking Algorithm To Improve The Stability Of The Output Behavior Of A Thermoelectric-Solar Hybrid Energy-Harvesting System

    Shapeable Maximum-Power Point-Tracking Algorithm To Improve The Stability Of The Output Behavior Of A Thermoelectric-Solar Hybrid Energy-Harvesting System by Md Yusop, Azdiana, Mohamed, Ramizi, Ayob, Afida, Mohamed, Azah

    Published 2017
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  18. 18
    Research Book - data engineering and information security series 1

    Research Book - data engineering and information security series 1

    Published 2017
    “…Chapter 3 proposes a new hybrid evolutionary algorithm for plant forecasting using fuzzy inference system. …”
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  19. 19
    The advantages of genetic algorithm and neural networks to forecast air pollution trend in Malaysia: an overview / Mohamad Idham Md Razak … [et al.]

    The advantages of genetic algorithm and neural networks to forecast air pollution trend in Malaysia: an overview / Mohamad Idham Md Razak … [et al.] by Md Razak, Mohamad Idham, Ahmad, Ismail, Bujang, Imbarine, Talib, Adi Hakim, Kedin, Nor Adila

    Published 2012
    “…Genetic Algorithms (GAs) are adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. …”
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  20. 20
    An Improved Evolutionary Algorithm in Formulating a Diet for Grouper

    An Improved Evolutionary Algorithm in Formulating a Diet for Grouper by Cai-Juan, Soong, Abd Rahman, Rosshairy, Ramli, Razamin

    Published 2023
    “…Hence, in this paper, an improved EA method known as the SR-SD-EA is proposed highlighting three important EA operators, which are initialization, selection and mutation. …”
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