Results 11 to 20 of about 315,009 (291)
Stock Price Prediction using Machine Learning and Swarm Intelligence [PDF]
Journal of Electrical and Computer Engineering Innovations, 2020 Background and Objectives: Stock price prediction has become one of the interesting and also challenging topics for researchers in the past few years.
I. Behravan, S. M. Razavi
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A Review of Quantum-Inspired Metaheuristic Algorithms for Automatic Clustering
Mathematics, 2023 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
Alokananda Dey +7 more
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Applied Sciences, 2022 Automatic clustering problems require clustering algorithms to automatically estimate the number of clusters in a dataset. However, the classical K-means requires the specification of the required number of clusters a priori.
Abiodun M. Ikotun, Absalom E. Ezugwu
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Journal of Hydroinformatics, 2023 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.
Zahra Alizadeh, Jafar Yazdi
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Automatically labeling hierarchical clusters [PDF]
Proceedings of the 2006 international conference on Digital government research, 2006 Government agencies must often quickly organize and analyze large amounts of textual information, for example comments received as part of notice and comment rulemaking. Hierarchical organization is popular because it represents information at different levels of detail and is convenient for interactive browsing. Good hierarchical clustering algorithms
Pucktada Treeratpituk, Jamie Callan
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Electronic Research Archive, 2023 In cluster analysis, determining the number of clusters is an important issue because there is less information about the most appropriate number of clusters in the real problem.
Zhuanzhe Zhao +6 more
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Automatic Clustering for Improved Radio Environment Maps in Distributed Applications
Applied Sciences, 2023 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,
Haithem Ben Chikha, Alaa Alaerjan
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An automatic density peaks clustering based on a density-distance clustering index
AIMS Mathematics, 2023 The density peaks clustering (DPC) algorithm plays an important role in data mining by quickly identifying cluster centers using decision graphs to identify arbitrary clusters. However, the decision graph introduces uncertainty in determining the cluster
Xiao Xu , Hong Liao, Xu Yang
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Consensus Nature Inspired Clustering of Single-Cell RNA-Sequencing Data
IEEE Access, 2022 Single-cell RNA sequencing (scRNA-seq) enables quantification of mRNA expression at the level of individual cells. scRNA-seq uncovers the disparity of cellular heterogeneity giving insights about the expression profiles of distinct cells revealing ...
Amany H. Abou El-Naga +3 more
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Clustering documents with active learning using Wikipedia [PDF]
, 2009 Wikipedia has been applied as a background knowledge base to various text mining problems, but very few attempts have been made to utilize it for document clustering. In this paper we propose to exploit the semantic knowledge in Wikipedia for clustering,
Frank, Eibe +3 more
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