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  1. 1

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…Moreover, experiments demonstrate that final clustering solution generated by the proposed incremental genetic-based clustering ensemble algorithm using the pattern ensemble learning method possess comparative or better clustering accuracy than clustering solutions generated by the incremental genetic-based clustering ensemble algorithms using other recombination operators. …”
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  2. 2

    An energy-efficient spectrum-aware reinforcement learning-based clustering algorithm for cognitive radio sensor networks by Mustapha, Ibrahim, Mohd Ali, Borhanuddin, A. Rasid, Mohd Fadlee, Sali, Aduwati, Mohamad, Hafizal

    Published 2015
    “…In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. …”
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    Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market by Hazirah Halul

    Published 2024
    “…Nowadays, Machine Learning (ML) can serve as one of the solutions to accelerate the process of decision-making in forecasting daily stock market price movements. …”
    thesis::master thesis
  5. 5

    Operating a reservoir system based on the shark machine learning algorithm by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, Ehteram, Mohammad, Hossain, Md Shabbir, El-Shafie, Ahmed

    Published 2018
    “…The SMLA began with a group of randomly produced potential solutions and later interactively executed the search for the optimal solution. …”
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  6. 6

    K-gen phishguard: an ensemble approach for phishing detection with k-means and genetic algorithm by Al-Hafiz, Ali Raheem, Jabir, Adnan J., Subramaniam, Shamala

    Published 2025
    “…In the first phase, the best set of features is identified by the Genetic algorithm and is utilised by the K-means clustering algorithm to divide the dataset into groups with similar traits. …”
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    Computerised Heuristic Algorithm for Multi-location Lecture Timetabling by Kuan, Huiggy

    Published 2020
    “…After that, the algorithm proceeds to Group Allocation Stage in a round robin optimisation. …”
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  11. 11

    Coherent crowd analysis with visual attributes / Nurul Japar by Nurul , Japar

    Published 2022
    “…As a result, the contributions of this thesis constitute more effective solutions for visual attributes extraction, coherent group detect and collectiveness analysis. …”
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  12. 12

    Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

    Published 2024
    “…Meta-heuristic algorithms are search techniques used to solve complexoptimization problems, and these algorithms can help provide reasonable solutions in a shorter time thanexact methods. …”
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  13. 13

    Optimal placement and sizing of FACTS devices for optimal power flow using metaheuristic optimizers by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2022
    “…These algorithms are selected from the different metaheuristics classification groups, where the implementation of these algorithms into the said problems will be tested on the modified IEEE 14-bus system. …”
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  14. 14

    Modeling a problem solving approach through computational thinking for teaching programming / Zebel Al Tareq by Zebel , Al Tareq

    Published 2021
    “…The syntax-based programming workshop was the control group. The problem-based and the game-based programming workshops utilizing our problem-solving model using sorting algorithms were the experimental groups. …”
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  15. 15

    A Review: Current Trend of Immersive Technologies for Indoor Navigation and the Algorithms by Sariman, Muhammad Shazmin, Othman, Maisara, Mat Akir, Rohaida, Mahamad, Abd Kadir, Ab Rahman, Munirah

    Published 2024
    “…Based on the findings of this review, we can conclude that an efficient solution for indoor navigation that uses the capabilities of embedded data and technological advances in immersive technologies can be achieved by training the shortest path algorithm with a deep learning algorithm to enhance the indoor navigation system.…”
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  16. 16

    Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

    Published 2019
    “…The basic component of the algorithm consists of several clans and each clan searches for the best place (or best solution) based on the position of their leader. …”
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  17. 17

    Investigating optimal smartphone placement for identifying stairs movement using machine learning by Muhammad Ruhul Amin, Shourov, Husman, Muhammad Afif, Toha, Siti Fauziah, Jasni, Farahiyah

    Published 2023
    “…The data was trained against 6 machine learning algorithms namely Decision Tree, Logistic Regression, Naive Bayes, Random Forest, Neural Networks and KNN. …”
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    Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

    Published 2012
    “…Among the available learning algorithms in the Neural Network Toolbox of MATLAB, three algorithms, gradient descent back propagation (TRAINGD), gradient descent with adaptive learning rule back propagation (TRAINGDA) and the Levenberg-Marquardt (TRAINLM) were studied. …”
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    Terrain awareness mobility model to support outdoor mobility for people with vision impairment by Yousef, Malkawi Abeer Dirar

    Published 2023
    “…TAM2 contains three main components; user model, terrain detection model, and learning model. For the prototyping phase, the study employed the deep learning detection framework YOLOv4-tiny algorithm to implement a real-time terrain detection model. …”
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