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, ...
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, ...
This project applies hierarchical clustering to group local authorities in England based on case closure reasons from the Children in Need Census (2013–2024). It supports benchmarking, policy ...
Alarm bells rang for the special master in the case, he said, when he used Westlaw to verify details in the briefing—only to discover, he said, that some of the quotations and court decisions cited by ...
my_range = np.arange(4) # parameter của arange xác định bằng số lượng phần tử của dataset (=len(x))tương ứng với 4 vị trí trên trục hoành; nếu data set có n phần tử thì my_range = np.arange(n) # their ...
Abstract: This paper introduces a codebook-based trellis-coded quantization (TCQ) approach utilizing K-means clustering, designed specifically for massive multiple-input multiple-output systems. The ...
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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