New 100 mg/dL Target Glucose setting offers more customization and tighter glucose management. Enhanced algorithm helps users remain in Automated Mode to improve the user experience. Most requested ...

Abstract: For radar signal sorting based on pulse descriptors, the inherent limitations of the traditional K-means algorithm include the requirement of a predefined number of clusters, the sensitivity ...

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 ...

Learn the Adagrad optimization algorithm, how it works, and how to implement it from scratch in Python for machine learning models. #Adagrad #Optimization #Python Here Are the States That Won't Tax ...

This project is my independent research into SAT solvers written entirely in Python, designed to explore the theory and practice of propositional satisfiability. It begins with a baseline DPLL ...

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 ...

What if you could create your very own personal AI assistant—one that could research, analyze, and even interact with tools—all from scratch? It might sound like a task reserved for seasoned ...

Implementation of the K-Means clustering algorithm from scratch using the FIFA 22 Complete Player Dataset to uncover player groupings based on performance and attributes.

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: The k-means method is widely utilized for clustering. Its simplicity, efficacy, and swiftness make it a favored choice among clustering algorithms. It faces the challenge of sensitivity to ...