Search Results - (( developing information clustering algorithm ) OR ( java application sensor algorithm ))

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  1. 1

    Extracting feature from images by using K-Means clustering algorithm / Abdul Hakim Zainal Abidin by Zainal Abidin, Abdul Hakim

    Published 2016
    “…This research scope are to develop a computer application that can extract meaningful information in images by implement KMeans clustering algorithm 10 self capture facial image will be use as the research subject to test the algorithm that will extracting meaningful information of the person. …”
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    Thesis
  2. 2

    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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    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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  5. 5

    The new efficient and accurate attribute-oriented clustering algorithms for categorical data by Qin, Hongwu

    Published 2012
    “…Many algorithms for clustering categorical data have been proposed, in which attribute-oriented hierarchical divisive clustering algorithm Min-Min Roughness (MMR) has the highest efficiency among these algorithms with low clustering accuracy, conversely, genetic clustering algorithm Genetic-Average Normalized Mutual Information (G-ANMI) has the highest clustering accuracy among these algorithms with low clustering efficiency. …”
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  6. 6

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

    Published 2016
    “…Density-based method has emerged as a worthwhile class for clustering data streams. Recently, a number of density-based algorithms have been developed for clustering data streams. …”
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    Article
  7. 7

    Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning by Masuyama, Naoki, Loo, Chu Kiong, Ishibuchi, Hisao, Kubota, Naoyuki, Nojima, Yusuke, Liu, Yiping

    Published 2019
    “…Other types of the ART-based topological clustering algorithms have been developed, however, these algorithms have various drawbacks such as a large number of parameters, sensitivity to noisy data. …”
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  8. 8

    The implementation of z-numbers in fuzzy clustering algorithm for wellness of chronic kidney disease patients by N. J., Mohd Jamal, Ku Muhammad Naim, Ku Khalif, Mohd Sham, Mohamad

    Published 2019
    “…Consequently, the implementation of z-numbers in fuzzy clustering algorithm is taken into consideration, where it has more authority to describe the knowledge of human being and extensively used in uncertain information development. …”
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  9. 9

    Reliability fuzzy clustering algorithm for wellness of elderly people by N. J., Mohd Jamal, Ku Muhammad Naim, Ku Khalif, Mohd Sham, Mohamad

    Published 2019
    “…Therefore, the implementation of z-numbers is taken into consideration, where it has more authority to describe the knowledge of human being and extensively used in uncertain information development. Thus, the objective of this paper is to propose a reliable fuzzy clustering algorithm using z-numbers. …”
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  10. 10

    Evaluation of the effectiveness of clustering algorithm in retrieving Malay documents / Aminah Mahmood by Mahmood, Aminah

    Published 2004
    “…This has led to an increased interest in developing methods that can help users to effectively navigate, summarize and organize this information with the ultimate goal of helping them to find what they are looking for. …”
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  11. 11

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

    Published 2021
    “…huge data is a big challenge. Clustering technique is able to find hidden patterns and to extract useful information from huge data. …”
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    Big Data Mining Using K-Means and DBSCAN Clustering Techniques by Fawzia Omer, A., Mohammed, H.A., Awadallah, M.A., Khan, Z., Abrar, S.U., Shah, M.D.

    Published 2022
    “…The density-based spatial clustering of applications with noise (DBSCAN) and the K-means algorithm were used to develop clustering algorithms. …”
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    Development Of Human Skin Detection Algorithm Using Multilayer Perceptron Neural Network And Clustering Method by Al-Mohair, Hani Kaid Saif

    Published 2017
    “…The Differential Evolution Algorithm (DE) is used in this work to select the optimum color and texture information to achieve the optimum response. …”
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  17. 17

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…The process begins through the monitoring of plants using sensors connected to the Arduino device. Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. …”
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    A novel hierarchical clustering algorithm for the analysis of 3D anthropometric data of the human head by Ellena, Thierry, Subic, Aleksandar, Mustafaa, Helmy, Yen, Pang Toh

    Published 2018
    “…A novel hierarchical algorithm was developed, in which a squared Euclidean metric was used to assess the head shape similarity of participants. …”
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    Minimizing the number of stunting prevalence using the euclid algorithm clustering approach by Zarlis, Muhammad, Oktavia, Tanty, Buaton, Relita, Ernawan, Ferda, Andrian, Kevin

    Published 2023
    “…The algorithm used is Euclid. The Euclid algorithm can cluster stunting prevalence data into 4 clusters with the very little category at 79%, the little category at 67%, the many categories at 51%, and the very much category at 21%. …”
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