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  1. 1
    Data clustering using the bees algorithm

    Data clustering using the bees algorithm by Pham, D.T, Otri, S., Afify, A., Mahmuddin, Massudi, Al-Jabbouli, H.

    Published 2007
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  2. 2
    Parallelization of noise reduction algorithm for seismic data on a beowulf cluster

    Parallelization of noise reduction algorithm for seismic data on a beowulf cluster by Aziz, I. A., Sandran, T., Haron, N. S., Hasan, M. H, Mehat, M.

    Published 2010
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  3. 3
    Support Vector Machines (SVM) in Test Extraction

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…Each word in the particular document is processed by both algorithms to determine its actual occurrence in the document by which it will first be clustered or grouped into categories based on parts of speech (verb, noun, adjective) which is done by K-Means, then later processed by SVM to determine the actual occurrence of each word in each of the cluster, taking into account whether the words have similar meanings with otherwords in the subsequent cluster. …”
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  4. 4
    Support Vector Machines (SVM) in Test Extraction

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…Each word in the particular document is processed by both algorithms to determine its actual occurrence in the document by which it will first be clustered or grouped into categories based on parts of speech (verb, noun, adjective) which is done by K-Means, then later processed by SVM to determine the actual occurrence of each word in each of the cluster, taking into account whether the words have similar meanings with otherwords in the subsequent cluster. …”
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  5. 5
    Density subspace clustering: a case study on perception of the required skill

    Density subspace clustering: a case study on perception of the required skill by Sembiring, Rahmat Widia

    Published 2014
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  6. 6
    Clustering of large time-series datasets using a multi-step approach / Saeed Reza Aghabozorgi Sahaf Yazdi

    Clustering of large time-series datasets using a multi-step approach / Saeed Reza Aghabozorgi Sahaf Yazdi by Yazdi, Saeed Reza Aghabozorgi Sahaf

    Published 2013
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  7. 7
    Cluster head selection algorithm using fuzzy logic in multi-tier Wireless Sensor Network for energy efficiency / Wan Isni Sofiah Wan Din

    Cluster head selection algorithm using fuzzy logic in multi-tier Wireless Sensor Network for energy efficiency / Wan Isni Sofiah Wan Din by Wan Din, Wan Isni Sofiah

    Published 2016
    “…Hence, this study proposes a new algorithm called Multi-Tier Protocol (MAP). MAP introduced clustering scheme to reduce the energy consumption of wireless sensor network in which, Fuzzy Logic used as tools to select the cluster head and multi-hop communication is used to route the data from the cluster head to the base station. …”
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  8. 8
    Enhancement of Ant System Algorithm for Course Timetabling Problem

    Enhancement of Ant System Algorithm for Course Timetabling Problem by Djamarus, Djasli

    Published 2009
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  9. 9
    Designing new chaotic and hyperchaotic systems for chaos-based cryptography

    Designing new chaotic and hyperchaotic systems for chaos-based cryptography by Kadhim, Al Karawi Hayder Natiq

    Published 2019
    “…To investigate its performance in terms of security, a new chaos-based image encryption algorithm is also proposed. …”
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  10. 10
    Optimisation model for scheduling MapReduce jobs in big data processing / Ibrahim Abaker Targio Hashem

    Optimisation model for scheduling MapReduce jobs in big data processing / Ibrahim Abaker Targio Hashem by Ibrahim Abaker , Targio Hashem

    Published 2017
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  11. 11
    Data Transformation Model For Addressing Incomplete And Inconsistent Quality Issues Of Big Data

    Data Transformation Model For Addressing Incomplete And Inconsistent Quality Issues Of Big Data by Onyeabor, Grace Amina

    Published 2024
    “…The complete and consistent data are put into clusters, and the designed algorithm predicts the position of any incomplete and inconsistent data, based on its value to be added to the specific cluster. …”
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  12. 12
    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier

    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier by Siow, Shien Loong

    Published 2018
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  13. 13
    Authentication-chains: blockchain-inspired lightweight authentication protocol for IoT networks

    Authentication-chains: blockchain-inspired lightweight authentication protocol for IoT networks by Al Ahmed, Mahmoud Tayseer, Hashim, Fazirulhisyam, Hashim, Shaiful Jahari, Abdullah, Azizol

    Published 2023
    “…A new consensus algorithm based on proof of identity authentication is adapted to the limited computational capabilities of IoT devices. …”
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  14. 14
    Analyzing enrolment patterns: modified stacked ensemble statistical learning based approach to educational decision-making

    Analyzing enrolment patterns: modified stacked ensemble statistical learning based approach to educational decision-making by Zun, Liang Chuan, Nursultan Japashov, Soon, Kien Yuan, Tan, Wei Qing, Noriszura Ismail

    Published 2024
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  15. 15
    A machine learning approach of predicting high potential archers by means of physical fitness indicators

    A machine learning approach of predicting high potential archers by means of physical fitness indicators by Muazu Musa, Rabiu, Abdul Majeed, Anwar P.P., Taha, Zahari, Chang, Siow Wee, Ab. Nasir, Ahmad Fakhri, Abdullah, Mohamad Razali

    Published 2019
    “…k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. However, the application of k-NN for prediction and classification in specific sport is still in its infancy. …”
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  16. 16
    A machine learning approach of predicting high potential archers by means of physical fitness indicators

    A machine learning approach of predicting high potential archers by means of physical fitness indicators by Musa, Rabiu Muazu, Anwar, P. P. Abdul Majeed, Zahari, Taha

    Published 2019
    “…k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. However, the application of k-NN for prediction and classification in specific sport is still in its infancy. …”
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  17. 17
    A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition

    A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

    Published 2002
    “…The rough sets vector quantization model proved its usefulness in the speech recognition framework, however it can be extended to different applications that involve large amounts of data such as speaker verification.…”
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  18. 18
    RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION

    RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION by CATUR ANDRYANI, NUR AFNY

    Published 2010
    “…This thesis proposes derivative free learning, using finite difference, methods for fixed size RBF network in comparison to gradient based learning for the application of system identification. …”
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  19. 19
    Power management system for smart microgrid considering meteorological and load demand data / Sam Koohikamali

    Power management system for smart microgrid considering meteorological and load demand data / Sam Koohikamali by Sam , Koohikamali

    Published 2015
    “…Microgrid is able to supply its local load based on operator decision and decline the power oscillations caused by solar photovoltaic (PV) plant together with variable loads. …”
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  20. 20
    Improved self-organizing map clustering of power transformer dissolved gas analysis using inputs pre-processing

    Improved self-organizing map clustering of power transformer dissolved gas analysis using inputs pre-processing by Misbahulmunir S., Ramachandaramurthy V.K., Thayoob Y.H.M.D.

    Published 2023
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