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  1. 1
    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
    “…Finally, we present a robust weighted kernel k-means algorithm incorporating spatial constraints for clustering spatial data as a case study. …”
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  2. 2
    Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting

    Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting by Ali, Noor Rasidah, Ku Mahamud, Ku Ruhana

    Published 2017
    “…Therefore, a clustering algorithm by introducing data transformation using X-means data splitting is proposed to investigate the spatial homogeneity of time series rainfall data. …”
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  3. 3
    A Clustering Algorithm for Evolving Data Streams Using Temporal Spatial Hyper Cube

    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
    “…To fill this gap, an online clustering algorithm for handling evolving data streams using a tempo?…”
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  4. 4
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
    “…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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  5. 5
    Cluster detection for spatio-temporal dengue cases at Selangor districts using multi-EigenSpot algorithm

    Cluster detection for spatio-temporal dengue cases at Selangor districts using multi-EigenSpot algorithm by Nor, N.H.M., Daud, H., Ullah, S.

    Published 2022
    “…Cluster detection is classified into three types of clustering groups, which are spatial clustering, temporal clustering, and spatio-temporal clustering. …”
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  6. 6
    Hybrid 2D phase unwrapping methodology using spatial fuzzy clustering and neurofuzzy classification with application in sar images

    Hybrid 2D phase unwrapping methodology using spatial fuzzy clustering and neurofuzzy classification with application in sar images by Then, Patrick Hang Hui.

    Published 2001
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  7. 7
    Framework for stream clustering of trajectories based on temporal micro clustering technique

    Framework for stream clustering of trajectories based on temporal micro clustering technique by Abdulrazzaq, Musaab Riyadh

    Published 2018
    “…The clustering algorithm consists of two components: the temporal micro-clusters generation and the temporal micro clusters merging. …”
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  8. 8
    Features extraction based on fuzzy clustering and segmentation onto the motion region for medium field surveillance application

    Features extraction based on fuzzy clustering and segmentation onto the motion region for medium field surveillance application by Maliki, Mohamad Nansah, Abu Bakar Al-Attas, Syed Abdul Rahman

    Published 2004
    “…Instead of using blob analysis, we believe that fuzzy based clustering algorithm, can also be used to generate different clusters. …”
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  9. 9
    Finding spatio-temporal patterns in climate data using clustering

    Finding spatio-temporal patterns in climate data using clustering by Md. Sap, Mohd. Noor, Awan, A. Majid

    Published 2005
    “…In this paper we present a robust weighted kernel k-means algorithm incorporating spatial constraints for clustering climate data. …”
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  10. 10
    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT

    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

    Published 2023
    “…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”
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  11. 11
    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning

    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

    Published 2016
    “…Beside that, classic bag of visual words algorithm (BoVW) is based on kmeans clustering and every SIFT feature belongs to one cluster and it leads to decreasing classification results. …”
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  12. 12
    Spatial-temporal analysis using two-stage clustering and GIS-based MCDM to identify potential market regions

    Spatial-temporal analysis using two-stage clustering and GIS-based MCDM to identify potential market regions by Ernawati, Kamal Baharin, Safiza Suhana, Kasmin, Fauziah

    Published 2021
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  13. 13
    Big Data Mining Using K-Means and DBSCAN Clustering Techniques

    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
    “…Results obtained after pre-processing phase showed that the data quality will improve when the number of records reduced by (51.45). 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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  14. 14
    RFID-enabled supply chain detection using clustering algorithms

    RFID-enabled supply chain detection using clustering algorithms by Azahar, T.F., Mahinderjit-Singh, M., Hassan, R.

    Published 2015
    “…Furthermore, RFID data nature characteristics faces the issues likes RFID just carry simple information, in-flood of data, inaccuracy data from RFID readers and difficulties to track spatial and place. We propose to use clustering algorithms in order to detect counterfeit in supply chain management. …”
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  15. 15
    Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm

    Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm by Vincent Chung, Hamzarul Alif Hamzah, Norah Tuah, Kit, Guan Lim, Min, Keng Tan, Kenneth Tze Kin Teo

    Published 2020
    “…Genetic-based evolutionary algorithms such as Genetic Algorithm (GA) and Differential Evolution (DE) have been popularly used to optimize cluster head selection in WSN to improve energy efficiency for the extension of network lifetime. …”
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  16. 16
    Clustering Based on Customers’ Behaviour in Accepting Personal Loan using Unsupervised Machine Learning

    Clustering Based on Customers’ Behaviour in Accepting Personal Loan using Unsupervised Machine Learning by Lim, Wai Ping, Goh, Ching Pang

    Published 2023
    “…As a conclusion, KMeans clustering was presenting better cluster results using this particular dataset.…”
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  17. 17
    A survey: Challenges of image segmentation based fuzzy c-means clustering algorithm

    A survey: Challenges of image segmentation based fuzzy c-means clustering algorithm by Alomoush W., Alrosan A., Norwawi N., Alomari Y., Albashish D., Almomani A., Alqahtani M.

    Published 2024
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  18. 18
    Machine learning for mapping and forecasting poverty in North Sumatera: a datadriven approach

    Machine learning for mapping and forecasting poverty in North Sumatera: a datadriven approach by Marpaung, Faridawaty, Ramadhani, Fanny, Dinata, Dewan

    Published 2024
    “…Poverty prediction was conducted using a random forest (RF) algorithm and poverty mapping was conducted using the K-Means algorithm. …”
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  19. 19
    Comparative spatial analysis of enteric fever and leptospirosis in Kelantan, Malaysia using e-notifikasi surveillance database, 2016 – 2022

    Comparative spatial analysis of enteric fever and leptospirosis in Kelantan, Malaysia using e-notifikasi surveillance database, 2016 – 2022 by Hatta, Hazlienor Mohd

    Published 2023
    “…Descriptive and spatial analyses were carried out including incidence and disease mapping, univariate and multitype point pattern analysis, spatial autocorrelation as well as spatial risk variation using spatstat, spdep, sparr, spatialEco and ggplot2 R packages inside RStudio IDE. …”
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  20. 20
    Rain streak removal using emboss and spatial-temporal depth filtering technique in video keyframes

    Rain streak removal using emboss and spatial-temporal depth filtering technique in video keyframes by Shariah, Sawsan Kamel

    Published 2012
    “…In this thesis rain streak have been captured and isolated from the background scene by using an embossed filter algorithm designed to highlight the transparent rain streaks that cause the blur and distortion of the video, while the removing algorithm is based on a simple algorithm that correlates spatio-temporal and depth of an image into one technique. …”
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