The K-shaped economy has returned, with gaps widening between high and low-income Americans. Higher earners see steadier opportunities, while lower-income households face cooler prospects. Some ...

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 ...

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: 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 ...

Abstract: The k-means algorithm is one of the most popular Machine learning clustering algorithms. This paper introduces a parallel k-means algorithm implementation for digit classification on ...

A K-Means algorithm implementation involving various optimization techniques. Used to group MNIST dataset of hand-written numbers 0-9.

Abstract: The k-means algorithm is a widely used Machine learning algorithm for clustering. This paper introduces a parallel k-means algorithm implementation for image classification. We implemented ...