Search Results - (( developing based clustering algorithm ) OR ( java application reoptimize algorithm ))

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  1. 1

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

    Published 2012
    “…So far, limited genetic-based clustering ensemble algorithms have been developed. …”
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    Thesis
  2. 2

    MuDi-Stream: A multi density clustering algorithm for evolving data stream by Amini, A., Saboohi, H., Herawan, T., Teh, Y.W.

    Published 2016
    “…Recently, a number of density-based algorithms have been developed for clustering data streams. …”
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    Article
  3. 3

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

    Published 2019
    “…In general, genetic based clustering algorithms showed the ability to reach near global optimal solution. …”
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    Thesis
  4. 4

    Clustering Methods For Cluster-Based Routing Protocols In Wireless Sensor Networks: Comparative Study by Hassan, Ali Abdul Hussian, Md Shah, Wahidah, Jabbar Mohammed, Ali Abdul, Othman, Mohd Fairuz Iskandar

    Published 2017
    “…These approaches of clustering algorithms whether Distributed, Centralized, or Hybrid are reviewed very well, since the most of clustering algorithms have been developed by many researches based on these approaches. …”
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    Article
  5. 5

    Metaheuristic multi-hop clustering optimization for energy-efficient wireless sensor network by Vincent Chung, Norah Tuah, Kit Guan Lim, Min Keng Tan, Ismail Saad, Kenneth Tze Kin Teo

    Published 2020
    “…Therefore, Genetic Algorithm-Cuckoo Search (GACS) is proposed and developed based on the multi-hop clustering model in this paper. …”
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    Article
  6. 6

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…In cluster labelling process, a cluster labelling algorithm based on calculation of minimum-distance (MD) between cluster mean and class mean was developed to label the clusters. …”
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    Thesis
  7. 7
  8. 8

    Web based clustering tool using K-MEAN++ algorithm / Muhammad Nur Syazwanie Aznan by Aznan, Muhammad Nur Syazwanie Aznan

    Published 2019
    “…Which is why this project objective is to develop a web based clustering tool using K-MEAN++ algorithm. …”
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    Thesis
  9. 9

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…In order to make the normal people can cluster their data easily, this project aims is to develop a web-based clustering tool that can be used by all peoples. …”
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    Thesis
  10. 10

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…In the software development testing we examine image based clustering, as we can used clustering by distance base, by pixel (red, green, blue) value etc., The problem is solved by region based method which is based on connect component and background detection techniques. …”
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    Thesis
  11. 11

    Cauchy Density-based Algorithm for VANETs Clustering in 3D Road Environments by AL-Obaidi, A.S., Jubair, M.A., Aziz, I.A., Ahmad, M.R., Mostafa, S.A., Mahdin, H., AL-Tickriti, A.T., Hassan, M.H.

    Published 2022
    “…In addition, a clustering algorithm that defines mobility vector and uses Cauchy-based density for enabling adding vehicles to their respective clusters. …”
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    Article
  12. 12

    Evaluation of FCV and FCM clustering algorithms in cluster-based compound selection by Sinarwati, Mohamad Suhaili, Mohamad Nazim, Jambli

    Published 2011
    “…One of most used clustering method is cluster-based compound selection, which involves subdividing a set of compounds into clusters and choosing one compound or a small number of compounds from each cluster. …”
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    Article
  13. 13

    An adaptive density-based method for clustering evolving data streams / Amineh Amini by Amini, Amineh

    Published 2014
    “…Due to these characteristics the traditional densitybased clustering is not applicable. Recently, a number of density-based algorithms have been developed for clustering data streams. …”
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    Thesis
  14. 14

    A soft hierarchical algorithm for the clustering of multiple bioactive chemical compounds by Salim, Naomie, Shah, J. Z.

    Published 2007
    “…The algorithm divides each and every cluster, if its size is larger than a pre-determined threshold, into two sub clusters based on the membership values of each structure. …”
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    Book Section
  15. 15

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

    Published 2021
    “…Besides, some real data sets were examined to validate the proposed algorithm. Empirical evidences based on simulated data sets indicated that the proposed modified k-means algorithm is able to recognise the optimum number of clusters for uncorrelated data sets. …”
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  16. 16

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

    Published 2007
    “…The authors’ team have developed a new population based search algorithm called the Bees Algorithm that is capable of locating near optimal solutions efficiently. …”
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    Conference or Workshop Item
  17. 17

    Aco-based feature selection algorithm for classification by Al-mazini, Hassan Fouad Abbas

    Published 2022
    “…The modified graph clustering ant colony optimisation (MGCACO) algorithm is an effective FS method that was developed based on grouping the highly correlated features. …”
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    Thesis
  18. 18

    A Clustering Algorithm for Evolving Data Streams Using Temporal Spatial Hyper Cube by Al?amri R., Murugesan R.K., Almutairi M., Munir K., Alkawsi G., Baashar Y.

    Published 2023
    “…Evaluation based on both the real world and synthetic datasets has proven the superiority of the developed BOCEDS TSHC clustering algorithm over the baseline algorithms with respect to most of the clustering met-rics. � 2022 by the authors. …”
    Article
  19. 19

    Development Of Fall Risk Clustering Algorithm In Older People by Wong, Kam Kang

    Published 2020
    “…Therefore, the aim of this study is to develop a clustering-based fall risk algorithm which can provide assistances for clinician in management of falls. …”
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    Final Year Project / Dissertation / Thesis
  20. 20

    Development of an effective clustering algorithm for older fallers by Goh, Choon Hian, Wong, Kam Kang, Tan, Maw Pin *, Ng, Siew Cheok, Chuah, Yea Dat, Kwan, Ban Hoe

    Published 2022
    “…The purpose of this study was, therefore, to develop a clustering-based algorithm to determine falls risk. …”
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    Article