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  1. 1
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…The K-means algorithm requires two inputs for it to be applied onto a data set, the value K, and a proximity measure. …”
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  2. 2
    Optimized clustering with modified K-means algorithm

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

    Published 2021
    “…In dealing with correlated variables, PCA was embedded in the proposed algorithm. The developed algorithms were tested on uncorrelated and correlated simulated data sets, generated under various conditions. …”
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  3. 3
    Efficient genetic partitioning-around-medoid algorithm for clustering

    Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

    Published 2019
    “…The rest sets of experiments carried out to evaluate the proposed algorithms. …”
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  4. 4
    A binary logarithm similarity measure with roughness approximation of rough neutrosophic set for Covid 19 cases / Muhammad Naim Haikal Yaso' and Hazlin Shahira Ramlee

    A binary logarithm similarity measure with roughness approximation of rough neutrosophic set for Covid 19 cases / Muhammad Naim Haikal Yaso' and Hazlin Shahira Ramlee by Yaso', Muhammad Naim Haikal, Ramlee, Hazlin Shahira

    Published 2022
    “…The objectives of this study are to define binary logarithm similarity measure for rough neutrosophic sets, to formulate the properties satisfied the binary logarithm similarity measure of rough and to develop a decision making model by using a binary logarithm similarity measure for case study (COVID 19). …”
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  5. 5
    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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  6. 6
    A heuristic approach for finding similarity indexes of multivariate data sets

    A heuristic approach for finding similarity indexes of multivariate data sets by Khan, Rahim, Zakarya, Muhammad, Khan, Ayaz Ali, Ur Rahman, Izaz, Abd Rahman, Mohd Amiruddin, Abdul Karim, Muhammad Khalis, Mustafa, Mohd Shafie

    Published 2020
    “…Experiments were conducted with both benchmark and real time MDSs for evaluating the proposed algorithm`s performance against its rival algorithms, which are traditional dynamic programming based and sequential similarity measure algorithms. …”
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  7. 7
    SURE-Autometrics algorithm for model selection in multiple equations

    SURE-Autometrics algorithm for model selection in multiple equations by Norhayati, Yusof

    Published 2016
    “…The SURE-Autometrics is also validated using two sets of real data by comparing the forecast error measures with five model selection algorithms and three non-algorithm procedures. …”
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  8. 8
    Algorithm analyzer to check the efficiency of codes

    Algorithm analyzer to check the efficiency of codes by Arvaree @ Alvar, Thamilvaani, Atan, Rodziah

    Published 2011
    “…Efficiency of codes developed is always an issue in software development. …”
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  9. 9
    Indoor Location Sensing Using WLAN IEEE 802.11b

    Indoor Location Sensing Using WLAN IEEE 802.11b by Moorthy, Sathis K., Yahya, Norashikin

    Published 2008
    “…The location sensing algorithm used for the system is the Nearest Neighbor (NN) algorithm. …”
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  10. 10
    Improving explicit aspects extraction in sentiment analysis using optimized ruleset / Mohammad Ahmad Jomah Tubishat

    Improving explicit aspects extraction in sentiment analysis using optimized ruleset / Mohammad Ahmad Jomah Tubishat by Mohammad Ahmad, Jomah Tubishat

    Published 2019
    “…The algorithm was then applied to the full set of 126 rules. …”
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  11. 11
    A binary logarithm similarity measure with roughness approximation of rough neutrosophic set for covid-19 / Suriana Alias …[et al.]

    A binary logarithm similarity measure with roughness approximation of rough neutrosophic set for covid-19 / Suriana Alias …[et al.] by Alias, Suriana, Mustapha, Norzieha, Md Yasin, Roliza, Abd Rhani, Norarida, Yaso, Muhammad Naim Haikal, Ramlee, Hazlin Shahira

    Published 2023
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  12. 12
    A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets

    A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets by Mohd Razali, Muhamad Hasbullah, Saian, Rizauddin, Yap, Bee Wah, Ku-Mahamud, Ku Ruhana

    Published 2021
    “…The proposed algorithm was compared to the existing algorithm, ATM in nine (9) publicly available imbalanced data sets. …”
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  13. 13
    Classification model for hotspot occurrences using spatial decision tree algorithm

    Classification model for hotspot occurrences using spatial decision tree algorithm by Sitanggang, Imas Sukaesih, Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin

    Published 2013
    “…As the ID3 algorithm that uses information gain in the attribute selection, the proposed algorithm uses spatial information gain to choose the best splitting layer from a set of explanatory layers. …”
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  14. 14
    Relevance detection and summarizing strategies identification algorithm using linguistic measures / Seyed Asadollah Abdiesfandani

    Relevance detection and summarizing strategies identification algorithm using linguistic measures / Seyed Asadollah Abdiesfandani by Seyed Asadollah, Abdiesfandani

    Published 2016
    “…In the second experiment, we want to measure the performance of the algorithm against human judgment to identify the summarizing strategies using the precision, recall, F-measure score and accuracy rate. …”
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  15. 15
    Chebyshev approximation of discrete polynomials and splines

    Chebyshev approximation of discrete polynomials and splines by Che Seman, Fauziahanim

    Published 2004
    “…The output of the algorithm is a set of extreme points that can be used to construct a minimal error approximation function. …”
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  16. 16
    Chebyshev approximation of discrete polynomials and splines

    Chebyshev approximation of discrete polynomials and splines by Che Seman, Fauziahanim

    Published 2004
    “…The output of the algorithm is a set of extreme points that can be used to construct a minimal error approximation function. …”
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  17. 17
    Real-time mass flow rate measurement for bulk solid flow using electrodynamic tomography system

    Real-time mass flow rate measurement for bulk solid flow using electrodynamic tomography system by Yaw, Wee Lee

    Published 2007
    “…The falling distance of material is set to 1.4 m. Linear back projection algorithm (LBP) and filtered back projection algorithm (FBP) are implemented for image reconstruction. …”
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  18. 18
    TOPSIS-based Regression Algorithms Evaluation

    TOPSIS-based Regression Algorithms Evaluation by Abu-Shareha, Ahmad Adel

    Published 2022
    “…Each of these applications has its own set of concerns, resulting in various metrics utilizations or those of similar measures but with diverse preferences. …”
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  19. 19
    Penilaian esei berbantukan komputer menggunakan teknik Bayesian dan pengunduran linear berganda

    Penilaian esei berbantukan komputer menggunakan teknik Bayesian dan pengunduran linear berganda by Mohamad @ Hamza, Mohd. Azwan

    Published 2006
    “…SLR Algorithm derive prediction of writing style using un-standardize feature set and size of features set not clearly defined and no warranty of significance in contribute to get closest grade prediction. …”
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  20. 20
    Experimenting the dendrite cell algorithm for disease outbreak detection model

    Experimenting the dendrite cell algorithm for disease outbreak detection model by Mohamad Mohsin, Mohamad Farhan, Hamdan, Abdul Razak, Abu Bakar, Azuraliza

    Published 2014
    “…The characteristics of early outbreak signal which are weak and behaved under uncertainties has brought to the development of outbreak detection model based on dendrite cell algorithm.Although the algorithm is proven can improve detection performance, it relies on several parameters which need to be defined before mining.In this study, the most appropriate parameter setting for outbreak detection using dendrite cell algorithm is examined.The experiment includes four parameters; the number of cell cycle update, the number of dendrite cell allowed to be in population, weight, and migration threshold value. …”
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