Abstract: Traditional k-means clustering is widely used to analyze regional and temporal variations in time series data, such as sea levels. However, its accuracy can be affected by limitations, ...
️ An intelligent system that takes a document and classifies different writing styles within the document using stylometric techniques.
Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...
Rocky high steep slopes are among the most dangerous disaster-causing geological bodies in large-scale engineering projects, like water conservancy and hydropower projects, railway tunnels, and metal ...
1 Department of Applied Sciences, Intelligent Asset Reliability Centre, Institute of Emerging Digital Technologies, Universiti Teknologi PETRONAS, Seri Iskandar, Malaysia 2 Bursa Malaysia Berhad, ...
The Atlanta-based carrier said it "always" complies with regulations. Airfare prices are traditionally dynamic due to an array of variable external factors from seasonal demand and jet fuel prices to ...
ABSTRACT: Clustering is an unsupervised machine learning technique used to organize unlabeled data into groups based on similarity. This paper applies the K-means and Fuzzy C-means clustering ...
ABSTRACT: Domaining is a crucial process in geostatistics, particularly when significant spatial variations are observed within a site, as these variations can significantly affect the outcomes of ...
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