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  1. 1
    Static and self-scalable filter range selection algorithms for peer-to-peer networks

    Static and self-scalable filter range selection algorithms for peer-to-peer networks by Kweh, Yeah Lun

    Published 2011
    “…Two multiple selection algorithm, which are known as “static filter range selection algorithm” and “self-scalable selection algorithm” are proposed. …”
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  2. 2
    Statistical fixed range multiple selection algorithm for peer-to-peer system

    Statistical fixed range multiple selection algorithm for peer-to-peer system by Kweh, Yeah Lun, Othman, Mohamed, Ahmad, Fatimah, Ibrahim, Hamidah

    Published 2010
    “…The algorithm is able to reduce the number of rounds needed and increase the success rate of all multiple selections in the selection process compared to the previous multiple selection algorithms proposed by Loo in 2005.…”
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  3. 3
    Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection

    Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection by Chia, Yee Shin

    Published 2015
    “…However this feature selection algorithm might be unstable due to the stochastic property of GA. …”
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  4. 4
    A New And Fast Rival Genetic Algorithm For Feature Selection

    A New And Fast Rival Genetic Algorithm For Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim

    Published 2021
    “…Moreover, a dynamic mutation rate is proposed to enhance the search behaviour of the algorithm in the mutation process. …”
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  5. 5
    Static range multiple selection algorithm for peer-to-peer system

    Static range multiple selection algorithm for peer-to-peer system by Othman, Mohamed, Kweh, Yeah Lun, Ahmad, Fatimah, Ibrahim, Hamidah

    Published 2011
    “…The algorithm is able to reduce the number of messages needed and increases the success rate of all multiple selections in the selection process compared to the previous multiple selection algorithms proposed by Loo in 2005.…”
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  6. 6
    Optimization of micro-end milling process parameters of titanium alloy using non-dominated sorting genetic algorithm

    Optimization of micro-end milling process parameters of titanium alloy using non-dominated sorting genetic algorithm by Golshan, Abolfazl

    Published 2013
    “…This study examines the effects of three process parameters which are spindle speed, feed rate and depth of cut on the process outputs. …”
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  7. 7
    Diabetes prediction system using clonal selection algorithm / Nor Aishah Mustapa

    Diabetes prediction system using clonal selection algorithm / Nor Aishah Mustapa by Mustapa, Nor Aishah

    Published 2012
    “…Diabetes Prediction system using clonal selection algorithm is available to test whether patients suffering from diabetes or not. …”
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  8. 8
    Extremal region selection for MSER detection in food recognition

    Extremal region selection for MSER detection in food recognition by Razali, Mohd Norhisham, Manshor, Noridayu, Abdul Halin, Alfian, Mustapha, Norwati, Yaakob, Razali

    Published 2021
    “…These interest points are considered as noises that lead to computation burden in the overall recognition process. Therefore, this research proposes an Extremal Region Selection (ERS) algorithm to improve MSER detection by reducing the number of irrelevant extremal regions by using unsupervised learning based on the k-means algorithm. …”
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  9. 9
    An enhancement of classification technique based on rough set theory for intrusion detection system application

    An enhancement of classification technique based on rough set theory for intrusion detection system application by Noor Suhana, Sulaiman

    Published 2019
    “…In order to improve classification performance problem, feature selection and discretization algorithm are crucial in selecting relevant attributes that could improve classification performance. …”
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  10. 10
    Optimization of attribute selection model using bio-inspired algorithms

    Optimization of attribute selection model using bio-inspired algorithms by Basir, Mohammad Aizat, Yusof, Yuhanis, Hussin, Mohamed Saifullah

    Published 2019
    “…Attribute selection which is also known as feature selection is an essential process that is relevant to predictive analysis.To date, various feature selection algorithms have been introduced, nevertheless they all work independently. …”
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  11. 11
    Extremal Region Selection for MSER Detection in Food Recognition

    Extremal Region Selection for MSER Detection in Food Recognition by Mohd Norhisham Razali @ Ghazali, Noridayu Manshor, Alfian Abdul Halin, Norwati Mustapha, Razali Yaakob

    Published 2021
    “…These interest points are considered as noises that lead to computation burden in the overall recognition process. Therefore, this research proposes an Extremal Region Selection (ERS) algorithm to improve MSER detection by reducing the number of irrelevant extremal regions by using unsupervised learning based on the k-means algorithm. …”
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  12. 12
    An optimum drill bit selection technique using artificial neural networks and genetic algorithms to increase the rate of penetration

    An optimum drill bit selection technique using artificial neural networks and genetic algorithms to increase the rate of penetration by Momeni, M., Hosseini, S.J., Ridha, S., Laruccia, M.B., Liu, X.

    Published 2018
    “…Drill bit is the most essential tool in drilling and drill bit selection plays a significant role in drilling process planning. …”
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  13. 13
    Optimization of cutting parameters to reduce cutting tool temperature in a dry turning process using genetic algorithm

    Optimization of cutting parameters to reduce cutting tool temperature in a dry turning process using genetic algorithm by Muhammad Waseem

    Published 2014
    “…The optimization has been carried out by manipulating the feed rate, depth of cut and cutting speed using Genetic Algorithm. …”
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  14. 14
    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
    “…Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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  15. 15
    Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis

    Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis by Asrul, Adam

    Published 2018
    “…The selection of parameters in grinding process remains as a crucial role to guarantee that the machined product quality is at the minimum production cost and maximum production rate. …”
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  16. 16
    Optimization of mycelium growth using genetic algorithm for multi-objective functions

    Optimization of mycelium growth using genetic algorithm for multi-objective functions by Muhamad Faiz, Abu Bakar

    Published 2019
    “…Through the implementation of selected multi-objective genetic algorithm, NSGA-ii was able to produce pareto front for optimizing both nitrogen concentration and the extension rate of the mycelium. …”
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  17. 17
    Identifying and detecting unlawful behavior in video images using genetic algorithm / Shahirah Mohamed Hatim

    Identifying and detecting unlawful behavior in video images using genetic algorithm / Shahirah Mohamed Hatim by Mohamed Hatim, Shahirah

    Published 2016
    “…Two types of selection parameter namely tournament selection (TOS) and random permutation selection (RPS) are chosen. …”
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  18. 18
    The implications for ahybrid detection technique against malicious sqlattacks on web applications

    The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

    Published 2025
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  19. 19
    An ensemble of neural network and modified grey wolf optimizer for stock prediction

    An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

    Published 2019
    “…The proposed approachoutperforms existing available meta-heuristic algorithms. Specifically, the proposed model achieved 97% classification rate, 95% precise prediction and less than 2.0 error rate. …”
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  20. 20
    Development of lung cancer prediction system using meta-heuristic optimized deep learning model

    Development of lung cancer prediction system using meta-heuristic optimized deep learning model by Mohamed Shakeel, Pethuraj

    Published 2023
    “…The algorithm detects the affected region depending on pixel similarity computation process. …”
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