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  1. 1
    Optimized clustering with modified K-means algorithm

    Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

    Published 2021
    “…Clustering technique is able to find hidden patterns and to extract useful information from huge data. Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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  2. 2
    Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm

    Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm by Dalatu, Paul Inuwa

    Published 2018
    “…It is attained successfully by combining the mean in K-Means algorithm, minimum and maximum in K-Midranges algorithm and compute their average as mean cluster of Hybrid mean. …”
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  3. 3
    Incorporating stemming algorithm in the Malay information retrieval that employs Thesaurus aproach / Mohd Rosmadi Mokhtar

    Incorporating stemming algorithm in the Malay information retrieval that employs Thesaurus aproach / Mohd Rosmadi Mokhtar by Mokhtar, Mohd Rosmadi

    Published 2001
    “…One of well-known conflation methods is stemming algorithms, where it is used to identify morphological variants. …”
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  4. 4
    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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  5. 5
    Enhancing latent semantic analysis (LSA) using tagging algorithm in retrieving Malay documents / Afiqah Bazlla Md Soom

    Enhancing latent semantic analysis (LSA) using tagging algorithm in retrieving Malay documents / Afiqah Bazlla Md Soom by Md Soom, Afiqah Bazlla

    Published 2018
    “…To investigate the enhancement of LSA using tagging algorithm (LSAT) in retrieving Malay documents, eight experiments are conducted in this research. …”
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  6. 6
    Improved normalization and standardization techniques for higher purity in K-means clustering

    Improved normalization and standardization techniques for higher purity in K-means clustering by Dalatu, Paul Inuwa, Fitrianto, Anwar, Mustapha, Aida

    Published 2016
    “…The K-means algorithm is a famous and fast technique in non-hierarchical cluster algorithms. …”
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  7. 7
    Detection of the spread of Covid-19 in Indonesia using K-Means Clustering Algorithm / Mohammad Yazdi Pusadan ... [et al.]

    Detection of the spread of Covid-19 in Indonesia using K-Means Clustering Algorithm / Mohammad Yazdi Pusadan ... [et al.] by Pusadan, Mohammad Yazdi, Rabbani, Mohammad Abied, Ardiansyah, Rizka, Ngemba, Hajra Rasmita

    Published 2023
    “…In this study, the method used is K-Means to perform clustering based on area grouping. …”
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  8. 8
    Gas Identi cation by Using a Cluster-k-Nearest-Neighbor

    Gas Identi cation by Using a Cluster-k-Nearest-Neighbor by Brahim Belhaouari, samir

    Published 2009
    “…We find 98.7% of accuracy in the classification of 6 different types of Gas by using K-means cluster algorithm and we find almost the same by using the new clustering algorithm.…”
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  9. 9
    Incorporating thesaurus in searching relevant ayat from the translated Al-Quran / Wan Iznif Wan Ibrahim

    Incorporating thesaurus in searching relevant ayat from the translated Al-Quran / Wan Iznif Wan Ibrahim by Wan Ibrahim, Wan Iznif

    Published 2002
    “…One of the well-known conflation algorithms, stemming, is only used to identify morphological variants. …”
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  10. 10
    An Analysis Of Various Algorithms For Text Spam Classification And Clustering Using Rapidminer And Weka

    An Analysis Of Various Algorithms For Text Spam Classification And Clustering Using Rapidminer And Weka by Zainal K., Sulaiman N.F., Jali M.Z.

    Published 2024
    “…By using the same dataset, which is downloaded from UCI, Machine Learning Repository, various algorithms used in classification and clustering in this simulation has been analysed comparatively. …”
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  11. 11
    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model

    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…EM and K-means clustering algorithms are used to cluster the multi-class classification attribute according to its relevance criteria and afterward, the clustered attributes are classified using an ensemble random forest classifier model. …”
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  12. 12
    Cluster optimization in VANET using MFO algorithm and K-Means clustering

    Cluster optimization in VANET using MFO algorithm and K-Means clustering by Ramlee, Sham Rizal, Hasan, Sazlinah, K. Subramaniam, Shamala

    Published 2023
    “…Proven to be an effective and efficient method for solving optimization problem. To design K-Means algorithm that portion nodes based on their proximities by optimize the distance between nodes within same cluster by assigning them to the closet cluster center. …”
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  13. 13
    All-pass filtered x least mean square algorithm for narrowband active noise control

    All-pass filtered x least mean square algorithm for narrowband active noise control by Mondal (Das), Kuheli, Das, Saurav, Abu, Aminudin, Hamada, Nozomu, Toh, Hoong Thiam, Das, Saikat, Faris, Waleed Fekry

    Published 2018
    “…Active noise control (ANC) is the most popular method for attenuating acoustic primary noise or disturbances by generating controllable secondary sources by which the output noise can be cancelled with the same amplitude but with opposite sign/sense. Most available ANC uses the secondary path modelling including filtered x least mean square (FxLMS) algorithm. …”
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  14. 14
    Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin

    Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

    Published 2014
    “…During the training process, bat algorithm is search the best one for number of neurons in hidden layer, learning rate and momentum rate which at the same time result the lowest mean absolute percentage error. …”
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  15. 15
    Segmentation of MRI brain images using statistical approaches

    Segmentation of MRI brain images using statistical approaches by Balafar, Mohammad Ali

    Published 2011
    “…Therefore, these algorithms can be improved upon. A neighbourhood-based noise-reduction algorithm which uses the edges of an image is proposed. …”
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  16. 16
    Effect of adopting different dispatching rules on the mean flow time in a two machine batch-shop problem

    Effect of adopting different dispatching rules on the mean flow time in a two machine batch-shop problem by Abdelraheem Elhaj, Hazir Farouk

    Published 2005
    “…This means that it is highly unlikely to find a polynomial algorithm to solve the problem. …”
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  17. 17
    The new efficient and accurate attribute-oriented clustering algorithms for categorical data

    The new efficient and accurate attribute-oriented clustering algorithms for categorical data by Qin, Hongwu

    Published 2012
    “…Four real-life data sets obtained from University of California Irvine (UCI) machine learning repository and ten synthetically generated data sets are used to evaluate MGR and IG-ANMI algorithms, and other four algorithms are used to compare with these two algorithms. …”
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  18. 18
    Power plant energy predictions based on thermal factors using ridge and support vector regressor algorithms

    Power plant energy predictions based on thermal factors using ridge and support vector regressor algorithms by Afzal, Asif, Alshahrani, Saad, Alrobaian, Abdulrahman, Buradi, Abdulrajak, Khan, Sher Afghan

    Published 2021
    “…This work aims to model the combined cycle power plant (CCPP) using different algorithms. The algorithms used are Ridge, Linear regressor (LR), and support vector regressor (SVR). …”
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  19. 19
    Optimization of the hidden layer of a multilayer perceptron with backpropagation (bp) network using hybrid k-means-greedy algorithm (kga) for time series prediction

    Optimization of the hidden layer of a multilayer perceptron with backpropagation (bp) network using hybrid k-means-greedy algorithm (kga) for time series prediction by Tan, James Yiaw Beng

    Published 2012
    “…We propose a model known as K-means-Greedy Algorithm (KGA) model in this research to overcome this serious drawback of the BP network. …”
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  20. 20
    Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin

    Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

    Published 2014
    “…During the training process, bat algorithm is search the best one for number of neurons in hidden layer, learning rate and momentum rate which at the same time result the lowest mean absolute percentage error. …”
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