Search Results - (( java implementation learning algorithm ) OR ( using spatial clustering algorithm ))
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Clustering Spatial Data Using a Kernel-Based Algorithm
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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Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting
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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A Clustering Algorithm for Evolving Data Streams Using Temporal Spatial Hyper Cube
Published 2023“…To fill this gap, an online clustering algorithm for handling evolving data streams using a tempo?…”
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Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm
Published 2008“…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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5
Cluster detection for spatio-temporal dengue cases at Selangor districts using multi-EigenSpot algorithm
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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Framework for stream clustering of trajectories based on temporal micro clustering technique
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
Features extraction based on fuzzy clustering and segmentation onto the motion region for medium field surveillance application
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
Finding spatio-temporal patterns in climate data using clustering
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
Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
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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Big Data Mining Using K-Means and DBSCAN Clustering Techniques
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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RFID-enabled supply chain detection using clustering algorithms
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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14
Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm
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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Clustering Based on Customers’ Behaviour in Accepting Personal Loan using Unsupervised Machine Learning
Published 2023“…As a conclusion, KMeans clustering was presenting better cluster results using this particular dataset.…”
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A survey: Challenges of image segmentation based fuzzy c-means clustering algorithm
Published 2024journal::journal article -
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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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18
Machine learning for mapping and forecasting poverty in North Sumatera: a datadriven approach
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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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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Comparative spatial analysis of enteric fever and leptospirosis in Kelantan, Malaysia using e-notifikasi surveillance database, 2016 – 2022
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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