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A web-based implementation of k-means algorithms
Published 2022“…The K-means algorithm requires two inputs for it to be applied onto a data set, the value K, and a proximity measure. …”
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Final Year Project / Dissertation / Thesis -
2
Clustering for binary data sets by using genetic algorithm-incremental K-means
Published 2018“…In conclusion, the GAIKM outperformed other clustering algorithms such as GCUK, IKM, Scalable K-means (SKM) and K-means clustering and paves the way for future research involving missing data and outliers.…”
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Article -
3
Autonomous and deterministic supervised fuzzy clustering
Published 2010“…This algorithm implements k-means to initialize the fuzzy model. …”
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Article -
4
Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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Thesis -
5
Cluster Analysis of Data Points using Partitioning and Probabilistic Model-based Algorithms
Published 2014“…Experiments were conducted using k-means, k-medoids and EM-algorithm. The study implements each algorithm using RapidMiner Software and the results generated was validated for correctness in accordance to the concept of external criteria method. …”
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Article -
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…The results showed that using canopy as a preprocessing step cut the time it proceeds to deal with the significant number of power load abnormalities found in parallel using a fast density peak dataset and the time it proceeds for the k-means algorithm to run. Additionally, tests demonstrate that combining canopy and the K-means algorithm to analyze data performs consistently and dependably on the Hadoop platform and has a clustering result that offers a scalable and effective solution for power system monitoring. ? …”
Article -
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Detection of the spread of Covid-19 in Indonesia using K-Means Clustering Algorithm / Mohammad Yazdi Pusadan ... [et al.]
Published 2023“…The purpose of this study is to apply the K-Means algorithm to perform clustering on COVID-19 data to determine the high spread of the virus in regions in Indonesia based on the frequency of the data. …”
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Book Section -
8
Modified artificial neural network (ANN) models for Malaysian construction costs indices (MCCI) data / Saadi Ahmad Kamaruddin
Published 2018“…Theoretically, the most common algorithm to train the network is the backpropagation (BP) algorithm which is based on the minimization of the ordinary least squares (LS) estimator in terms of mean squared error (MSE). …”
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Book Section -
9
A study of fluctuations and confidence of implementation in genetic algorithm optimized network in data centre
Published 2018“…Study of fluctuation in genetic algorithm has been a sub-objective in genetic algorithm implementations. …”
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Article -
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A study of fluctuations and confidence of implementation in genetic algorithm optimized network in data centre
Published 2018“…Study of fluctuation in genetic algorithm has been a sub-objective in genetic algorithm implementations. …”
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Article -
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Implementation of perez-dumortier calibration algorithm
Published 2014“…To avoid the unnecessary needs to travel to high altitude for sunphotometers calibration, Perez-Dumotier calibration algorithm has been used as an objective means to select the right intensity data so that the calibration can be performed at any altitude levels. …”
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Chapter In Book -
12
MGR: An Information Theory Based Hierarchical Divisive Clustering Algorithm for Categorical Data
Published 2014“…This research proposes mean gain ratio (MGR), a new information theory based hierarchical divisive clustering algorithm for categorical data. …”
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Article -
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Widely linear dynamic quaternion valued least mean square algorithm for linear filtering
Published 2017“…The performance of the proposed algorithms are compared with quaternion least mean square QLMS, zero-attract quaternion least mean square ZA-QLMS, and widely linear quaternion least mean square WL-QLMS algorithms. …”
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Thesis -
14
Data hiding in medical images using encryption and steganography techniques
Published 2019“…This paper presents securing the transmission of medical images over the Internet. The presented algorithms will be applied to medical data. This work presents a method that combines encryption, steganography and compression techniques for data transmission purpose. …”
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Undergraduates Project Papers -
15
Performance evaluation of different data aggregation algorithms for different types of sensors in WSN based cluster
Published 2018“…The algorithms applied separately with (1) Mean (2) Median (3) Mode (4) Geometric mean (5) Harmonic mean. …”
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Thesis -
16
Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin
Published 2014“…In other words, the implemented bat algorithm in neural network structure is to get global optimization in order to minimize mean absolute percentage error, MAPE. …”
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Article -
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Modeling of vehicle trajectory using K-means and fuzzy C-means clustering
Published 2019“…Hence, the clustering of vehicle trajectory dataset for similar patterns identification is implemented with k-means and fuzzy c-means (FCM) clustering algorithm. …”
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Proceedings -
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Group method of data handling with artificial bee colony in combining forecasts
Published 2018“…The weights for each individual model are calculated using ABC algorithm. In order to evaluate the proposed model, this study tested the proposed model on the International Airline Passengers data, and the performances are calculated using mean square error (MSE), mean average error (MAE) and mean average percentage error (MAPE). …”
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Article -
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
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Thesis -
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