This study investigates the application of advanced clustering methods to geological fracture analysis in the Baba Kohi anticline, located in the folded Zagros region of southwest Iran. The primary ...
As a highly contagious respiratory disease, influenza exhibits significant spatiotemporal fluctuations in incidence, posing a persistent threat to public health and placing considerable strain on ...
Accurately identifying fracture zones and their types in strata is of great significance for enhancing oil and gas recovery efficiency. Due to its complicated geological structure and long-term ...
Abstract: This paper proposes an improved K-means clustering algorithm based on density-weighted Canopy to address the efficiency bottlenecks and clustering accuracy issues commonly encountered by ...
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 algorithms to a ...
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, ...
Accurate LAI estimation of soybean plants in the field using deep learning and clustering algorithms
National Key Laboratory for Tropical Crop Breeding, Sanya Research Institute of Hainan University, Hainan University, Sanya, China The leaf area index (LAI) is a critical parameter for characterizing ...
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