An enhanced k-means clustering algorithm for pattern discovery in healthcare data حسب Haraty, Ramzi A.

"…This paper studies data mining applications in healthcare. Mainly, we study k-means clustering algorithms on large datasets and present an enhancement to k-means clustering, which requires k or a lesser number of passes to a dataset. …"
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DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data حسب Assaf, Ali

"…In this work, we present DG-means, which is a greedy algorithm that performs on distributed sets of data. …"
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Efficient Approximate Conformance Checking Using Trie Data Structures حسب Awad, Ahmed

الموضوعات: "…Estimation error,Runtime,Computational modeling,Data structures,Approximation algorithms,Encoding,Computational efficiency…"
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Design of acoustic absorbing metasurfaces using a data-driven approach حسب Hamza Baali (14603380)

الموضوعات:

An efficient and secure compression technique for data protection using burrows-wheeler transform algorithm حسب M Baritha Begum (17541483)

The unified effect of data encoding, ansatz expressibility and entanglement on the trainability of HQNNs حسب Muhammad Kashif (3923483)

"…We focus on the combined influence of data encoding, qubit entanglement, and ansatz expressibility in hybrid quantum neural networks (HQNNs) for multi-class classification tasks. …"

Convergence behavior of the normalized least mean fourth algorithm حسب Zerguine, A.

"…The normalized least mean fourth (NLMF) algorithm is presented in this work and shown to have potentially faster convergence. …"
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A FAMILY OF NORMALIZED LEAST MEAN FOURTH ALGORITHMS حسب Zerguine, Azzedine

"…In this work, a family of normalized least mean fourth algorithms is presented. Unlike the LMF algorithm, the convergence behavior of these algorithms is independent of the input data correlation statistics. …"
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Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm حسب Nasser, Youssef

"…This work aims to enhance the performance of the K-means algorithm by introducing a novel method for selecting the initial centroids, thereby minimizing randomness and reducing the number of iterations needed to reach optimal results. …"
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Convergence and steady-state analysis of the normalized least mean fourth algorithm حسب Zerguine, Azzedine

"…The normalized least mean-fourth (NLMF) algorithm is presented in this work and shown to have potentially faster convergence. …"

Convergence and steady-state analysis of the normalized least mean fourth algorithm حسب Zerguine, Azzedine

"…The normalized least mean-fourth (NLMF) algorithm is presented in this work and shown to have potentially faster convergence. …"
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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT حسب Dhananjay Bisen (19482454)

الموضوعات:

Simulated tempering and mean field annealing for mapping to multicomputers. (c1996) حسب Aghazarian, Gabriel I.

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Cluster-based anonymity model and algorithm for 1:1 dataset with a single sensitive attribute using machine learning technique حسب J. Jayapradha (21323774)

Random Forest Bagging and X‐Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data حسب Rajesh Kumar Dhanaraj (19646269)

"…<p dir="ltr">In the current ongoing crisis, people mostly rely on mobile phones for all the activities, but query analysis and mobile data security are major issues. Several research works have been made on efficient detection of antipatterns for minimizing the complexity of query analysis. …"

A FUZZY EVOLUTIONARY ALGORITHM FOR TOPOLOGY DESIGN OF CAMPUS NETWORKS حسب Youssef, H.

"…In this paper, we present a Simulated Evolution algorithm for the design of campus network topology. …"
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A Parallel Neural Networks Algorithm for the Clique Partitioning Problem حسب Harmanani, Haidar M.

"…The proposed algorithm has a time complexity of O(1) for a neural network with n vertices and c cliques. …"
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A Survey of Data Clustering Techniques حسب Sobeh, Salma

"…This survey examines seven widely recognized clustering techniques, namely k-means, G-means, DBSCAN, Agglomerative hierarchical clustering, Two-stage density (DBSCAN and k-means) algorithm, Two-levels (DBSCAN and hierarchical) clustering algorithm, and Two-stage MeanShift and K-means clustering algorithm and compares them over a real dataset - The Blockchain dataset, including prominent cryptocurrencies like Binance, Bitcoin, Doge, and Ethereum, under several metrics such as silhouette coefficient, Calinski-Harabasz, Davies-Bouldin Index, time complexity, and entropy.…"
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How can algorithms help in segmenting users and customers? A systematic review and research agenda for algorithmic customer segmentation حسب Joni Salminen (7434770)

Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm حسب Youssef, H.

"…The problem consists of deciding the number, types, and locations of the network active elements (hubs, switches, and routers), as well as the links and their capacities. …"
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