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  1. 1
    Finding an effective classification technique to develop a software team composition model

    Finding an effective classification technique to develop a software team composition model by Gilal, A.R., Jaafar, J., Capretz, L.F., Omar, M., Basri, S., Aziz, I.A.

    Published 2018
    “…Based on the results, the Johnson algorithm (JA) of RST appeared to be an effective technique for a team composition model. …”
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  2. 2
    Finding an effective classification technique to develop a software team composition model

    Finding an effective classification technique to develop a software team composition model by Gilal, A.R., Jaafar, J., Capretz, L.F., Omar, M., Basri, S., Aziz, I.A.

    Published 2018
    “…Based on the results, the Johnson algorithm (JA) of RST appeared to be an effective technique for a team composition model. …”
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  3. 3
    Detection of tube defect using the autoregressive algorithm

    Detection of tube defect using the autoregressive algorithm by Abd Halim, Zakiah, Jamaludin, Nordin, Junaidi, Syarif, Syed Yusainee, Syed Yahya

    Published 2015
    “…This study is aimed to automate defect detection using the pattern recognition approach based on the classification of high frequency stress wave signals. …”
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  4. 4
    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan

    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

    Published 2020
    “…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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  5. 5
    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using k-Nearest Neighbour (k-NN)

    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using k-Nearest Neighbour (k-NN) by Mohamad Hushnie, Haron, Nur Azzimah, Zamri, Khairunisa, Muthusamy

    Published 2023
    “…Next, the grades of concrete were classified using a machine learning algorithm named k-Nearest Neighbour (k-NN). …”
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  6. 6
    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using kNearest Neighbour (k-NN)

    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using kNearest Neighbour (k-NN) by Mohamad Hushnie, Haron, Nur Azzimah, Zamri, Khairunisa, Muthusamy

    Published 2023
    “…Next, the grades of concrete were classified using a machine learning algorithm named k-Nearest Neighbour (k-NN). …”
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  7. 7
    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition

    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…In pattern recognition system, achieving high accuracy in pattern classification is crucial. …”
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  8. 8
    The classification of urban growth pattern using topological relation border length algorithm: An experimental study

    The classification of urban growth pattern using topological relation border length algorithm: An experimental study by Ghani N.L.A., Abidin S.Z.Z.

    Published 2023
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  9. 9
    Pattern Recognition for Human Diseases Classification in Spectral Analysis

    Pattern Recognition for Human Diseases Classification in Spectral Analysis by Nur Hasshima Hasbi, Abdullah Bade, Fuei, Pien Chee, Muhammad Izzuddin Rumaling

    Published 2022
    “…The use of UV/Vis, IR, and Raman spectroscopy for disease classification is also highlighted. To conclude, many pattern recognition algorithms have the potential to overcome each of their distinct limits, and there is also the option of combining all of these algorithms to create an ensemble of methods.…”
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  10. 10
    The Potential of a Classification-based Algorithm to Calculate Calories in Real-Time Via Pattern Recognition

    The Potential of a Classification-based Algorithm to Calculate Calories in Real-Time Via Pattern Recognition by M. A., Ameedeen, Marhaini, M. S.

    Published 2016
    “…While the algorithm helped to classify different types of wavelengths produced from the sensor, a classification-based algorithm via Pattern Recognition Method will be used to classify and match the food components. …”
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  11. 11
    Experimental study of urban growth pattern classification using moving window algorithm

    Experimental study of urban growth pattern classification using moving window algorithm by Ghani N.L.A., Abidin S.Z.Z.

    Published 2023
    “…Moving window algorithm determines urban growth pattern based on moving window analysis and a set of classification rules. …”
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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
    “…There are a lot of feature extraction methods and classification methods for iris classification. Classic local binary pattern (LBP) is one of the most useful feature extraction methods. …”
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  13. 13
    Songket pattern classification using backpropagation neural network / Nik Aidil Syawalni Nik Mazlan

    Songket pattern classification using backpropagation neural network / Nik Aidil Syawalni Nik Mazlan by Nik Mazlan, Nik Aidil Syawalni

    Published 2024
    “…The study's outcomes underscore the capability of the BPNN-based algorithm to attain remarkable accuracy in Songket pattern classification, thus showcasing its viability for real-world applications.…”
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  14. 14
    Hybrid ACO and SVM algorithm for pattern classification

    Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

    Published 2013
    “…Support Vector Machine (SVM) is a pattern classification approach originated from statistical approaches. …”
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  15. 15
    A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification

    A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification by Quteishat, A., Lim, C.P., Tan, K.S.

    Published 2010
    “…In this paper, a two-stage pattern classification and rule extraction system is proposed. …”
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  16. 16
    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach

    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach by Moheb Pour, Majid Reza

    Published 2009
    “…Pattern recognition/classification has received a considerable attention in engineering fields. …”
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  17. 17
    Genetic algorithm fuzzy logic for medical knowledge-based pattern classification

    Genetic algorithm fuzzy logic for medical knowledge-based pattern classification by Tan, Chin Hooi, Tan, Mei Sze, Chang, Siow Wee, Yap, Keem Siah, Yap, Hwa Jen, Wong, Shen Yuong

    Published 2018
    “…The proposed algorithm was applied and tested in four critical illness datasets in medical knowledge pattern classification. …”
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  18. 18
    A hybrid-based modified adaptive fuzzy inference engine for pattern classification

    A hybrid-based modified adaptive fuzzy inference engine for pattern classification by Sayeed, Md. Shohel, Ramli, Abdul Rahman, Hossen, Md. Jakir, Samsudin, Khairulmizam, Rokhani, Fakhrul Zaman

    Published 2011
    “…The Neuro-Fuzzy hybridization scheme has become of research interest in pattern classification over the past decade. The present paper proposes a hybrid Modified Adaptive Fuzzy Inference Engine (MAFIE) for pattern classification. …”
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  19. 19
    MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM

    MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM by Aurangzeb, khan, Baharum, Baharudin, Khairullah, khan

    Published 2011
    “…Classification and patterns extraction from customer data is very important for business support and decision making. …”
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    Citation Index Journal
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  20. 20
    Quantitative spasticity assessment model of neurological disorder patients / AA Puzi … [et al.]

    Quantitative spasticity assessment model of neurological disorder patients / AA Puzi … [et al.] by Ahmad Puzi, Asmarani, Aliff-Imran, M.D., Zainuddin, Ahmad Anwar, Basri, Atikah Balqis, Mohd Khairuddin, Ismail

    Published 2023
    “…The cues from the MMG signals pattern will be used to select the sampling features for the development of the classification algorithm model. …”
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