Search Results - (( pattern clustering algorithm ) OR ((( pattern based algorithm ) OR ( patterns new algorithm ))))

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  1. 1
    A numerical method for frequent pattern mining

    A numerical method for frequent pattern mining by Mustapha, Norwati, Nadimi-Shahraki, Mohammad-Hossein, Mamat, Ali, Sulaiman, Md. Nasir

    Published 2009
    “…There are two new properties introduced in this method; a novel tree structure called PC_Tree and PC_Miner algorithm. …”
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  2. 2
    Clustering Spatial Data Using a Kernel-Based Algorithm

    Clustering Spatial Data Using a Kernel-Based Algorithm by Awan, A. Majid, Md. Sap, Mohd. Noor

    Published 2005
    “…Therefore, this work comes up with new clustering algorithm using kernel-based methods for effective and efficient data analysis by exploring structures in the data.…”
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  3. 3
    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
    “…In this project, a classification system is proposed with the one-dimensional local binary pattern algorithm (1D-LBP) with the K-Nearest Neighbour (K-NN) classifier and the system is developed by using a Raspberry Pi 3.There are eight different subjects used to classify in this classification system and each subject consists of seven samples of normalized iris image as input to the system. …”
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  4. 4
    USING LATENT SEMANTIC INDEXING FOR DOCUMENT CLUSTERING

    USING LATENT SEMANTIC INDEXING FOR DOCUMENT CLUSTERING by MUFLIKHAH, LAILIL

    Published 2010
    “…Based on the new representation, the documents are then subjected to the clustering algorithm itself, which is Fuzzy c-Means algorithm. …”
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  5. 5
    Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman

    Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman by Seman, Ali

    Published 2013
    “…The idea was incorporated into a new algorithm called, k-Approximate Modal Haplotypes (&-AMH) algorithm. …”
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  6. 6
    Application of Optimization Methods for Solving Clustering and Classification Problems

    Application of Optimization Methods for Solving Clustering and Classification Problems by Shabanzadeh, Parvaneh

    Published 2011
    “…The data vectors are assigned to the closest cluster and correspondingly to the set, which contains this cluster and an algorithm based on a derivative-free method is applied to the solution of this problem. …”
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  7. 7
    An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction

    An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction by Ahanin, Fatemeh

    Published 2023
    “…MDL uses patterns to express the repeated presence in the data of particular items or clusters. …”
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  8. 8
    High performance in minimizing of term-document matrix representation for document clustering

    High performance in minimizing of term-document matrix representation for document clustering by B., Baharudin, L., Muflikhah

    Published 2009
    “…By using various numbers of patterns (rank) of SVD, the proposed method is applied to cluster documents using the Fuzzy C-Means algorithm. …”
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  9. 9
    A Novel Soft Set Approach in Selecting Clustering Attribute

    A Novel Soft Set Approach in Selecting Clustering Attribute by Qin, Hongwu, Ma, Xiuqin, Jasni, Mohamad Zain, Herawan, Tutut

    Published 2012
    “…Furthermore, we use it to select a clustering attribute for categorical datasets and a heuristic algorithm is presented. …”
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  10. 10
    Clustering ensemble learning method based on incremental genetic algorithms

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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  11. 11
    Neural network-based codebook search for image compression

    Neural network-based codebook search for image compression by Bodruzzaman, M., Gupta, R., Karim, M.R., Bodruzzaman, S.

    Published 2000
    “…The codebook is analyzed to identify a pattern in the codebook. This pattern is used to train a neural network to obtain the approximate index of the pattern in the codebook. …”
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  12. 12
    A green clustering protocol for mobile sensor network using particle swarm optimization

    A green clustering protocol for mobile sensor network using particle swarm optimization by Latiff, N.M.A., NikAbdMalik, N., Latiff, A.H.A.

    Published 2016
    “…We also take into account the mobility factor when defining the cluster membership, so that the sensor nodes can join the cluster that has the similar mobility pattern. …”
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  13. 13
    A green clustering protocol for mobile sensor network using particle swarm optimization

    A green clustering protocol for mobile sensor network using particle swarm optimization by Latiff, N.M.A., NikAbdMalik, N., Latiff, A.H.A.

    Published 2016
    “…We also take into account the mobility factor when defining the cluster membership, so that the sensor nodes can join the cluster that has the similar mobility pattern. …”
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  14. 14
    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor

    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor by Brahim Belhaouari, samir

    Published 2009
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  15. 15
    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor

    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor by Brahim Belhaouari, samir

    Published 2008
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  16. 16
    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
    “…It overcomes the limitations of conventional clustering algorithms in dealing with time-series data. …”
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  17. 17
    Local-based stereo matching algorithm using multi-cost pyramid fusion, hybrid random aggregation and hierarchical cluster-edge refinement

    Local-based stereo matching algorithm using multi-cost pyramid fusion, hybrid random aggregation and hierarchical cluster-edge refinement by Kadmin, Ahmad Fauzan

    Published 2023
    “…The estimation of Stereo Matching Algorithm (SMA) is one of the extensive research topics for obtaining the disparity map from two images. …”
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  18. 18
    Web user navigation pattern mining approach based on graph partitioning algorithm.

    Web user navigation pattern mining approach based on graph partitioning algorithm. by Jalali, Mehrdad, Mustapha, Norwati, Mamat, Ali, Sulaiman, Md. Nasir

    Published 2008
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  19. 19
    The Effect Of Linkages In The Hierarchical Clustering Of Auto-Regressive Algorithm For Defect Identification In Heat Exchanger Tubes

    The Effect Of Linkages In The Hierarchical Clustering Of Auto-Regressive Algorithm For Defect Identification In Heat Exchanger Tubes by Abd Halim, Zakiah, Jamaludin, Nordin, Putra, Azma

    Published 2019
    “…Pattern recognition approach based on Auto-Regressive (AR) algorithm is an alternative way to provide a more accurate defect identification from stress wave propagated along ASTM A179 heat exchanger tubes. …”
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  20. 20
    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
    “…In this paper we proposed an algorithm for mining patterns of huge stock data to predict factors affecting the sale of products. …”
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