An improved differential evolution with cluster decomposition algorithm for automatic clustering
Sign Up to like & getrecommendations! Published in 2019 at "Soft Computing"
DOI: 10.1007/s00500-018-3496-z
Abstract: This study proposes an improved differential evolution (DE) algorithm to solve an automatic clustering problem. Automatic clustering is a clustering technique in data mining which can automatically define the best number of clusters, as well… read more here.
Keywords: automatic clustering; algorithm automatic; improved differential; differential evolution ... See more keywords
A Density-Center-Based Automatic Clustering Algorithm for IoT Data Analysis
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2022.3194886
Abstract: With the rapid development of Internet of Things (IoT), much data has been produced, and new requirements have been posed for data mining. Clustering plays an essential role in discovering the underlying patterns of IoT… read more here.
Keywords: density; center based; density center; iot data ... See more keywords
A Framework of Automatic Clustering and Tracking for Time-Variant Multipath Components
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DOI: 10.1109/lcomm.2016.2637364
Abstract: A framework of automatic clustering and tracking algorithm is proposed for the multipath components (MPCs) in time-variant radio channels. The algorithm is based on the channel dynamics in time domain and is able to reflect… read more here.
Keywords: multipath components; framework automatic; clustering tracking; automatic clustering ... See more keywords
Boosting k-means clustering with symbiotic organisms search for automatic clustering problems
Sign Up to like & getrecommendations! Published in 2022 at "PLoS ONE"
DOI: 10.1371/journal.pone.0272861
Abstract: Kmeans clustering algorithm is an iterative unsupervised learning algorithm that tries to partition the given dataset into k pre-defined distinct non-overlapping clusters where each data point belongs to only one group. However, its performance is… read more here.
Keywords: organisms search; boosting means; symbiotic organisms; automatic clustering ... See more keywords
Calibration of hydrological models for ungauged catchments by automatic clustering using a differential evolution algorithm: the Gorganrood river basin case study
Sign Up to like & getrecommendations! Published in 2023 at "Journal of Hydroinformatics"
DOI: 10.2166/hydro.2023.081
Abstract: The hydrological model calibration is a challenging task, especially in ungauged catchments. The regionalization calibration methods can be used to estimate the parameters of the model in ungauged sub-catchments. In this article, the model of… read more here.
Keywords: calibration; evolution algorithm; differential evolution; ungauged catchments ... See more keywords
Automatic Clustering for Improved Radio Environment Maps in Distributed Applications
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DOI: 10.3390/app13105902
Abstract: Wireless communication greatly contributes to the evolution of new technologies, such as the Internet of Things (IoT) and edge computing. The new generation networks, including 5G and 6G, provide several connectivity advantages for multiple applications,… read more here.
Keywords: distributed applications; environment maps; automatic clustering; radio environment ... See more keywords
A Review of Quantum-Inspired Metaheuristic Algorithms for Automatic Clustering
Sign Up to like & getrecommendations! Published in 2023 at "Mathematics"
DOI: 10.3390/math11092018
Abstract: In real-world scenarios, identifying the optimal number of clusters in a dataset is a difficult task due to insufficient knowledge. Therefore, the indispensability of sophisticated automatic clustering algorithms for this purpose has been contemplated by… read more here.
Keywords: automatic clustering; inspired metaheuristic; metaheuristic algorithms; quantum inspired ... See more keywords