Scientific Research Publishing

Datta, T. and Ghosh, I. (2015) Using Clustering Method to Understand Indian Stock Market Volatility. Communications on Applied Electronics, 2, 35-44.

ABSTRACT: This paper proposes a hybrid AI framework that integrates technical indicators, fundamental data, and financial news sentiment into a stacked ensemble learning model. The ensemble combines ...
Phys.org

Potentially distinct structure in Kuiper belt discovered with help of clustering algorithm

A vast region of our solar system, called the Kuiper belt, stretches from the orbit of Neptune out to 50 or so astronomical units (AU), where an AU is the distance between Earth and the sun. This ...
eLife

Single-cell transcriptome sequencing for opening the blood-brain barrier through specific mode electroacupuncture stimulation

This paper reports a valuable discovery that specific-mode electroacupuncture (EA) transiently opens the blood-brain barrier (BBB) in rats. The evidence is solid but lacks functional validation of BBB ...
Frontiers

Elucidating the multiscale mechanisms and therapeutic targets of caffeic acid in gastric cancer: a synergy of computational and experimental approaches

1 School of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, Anhui, China 2 The First Affiliated Hospital, Anhui University of Chinese Medicine, Hefei, Anhui, China ...
IEEE

An Enhanced Density Peak Clustering Algorithm With Dimensionality Reduction and Relative Density Normalization for High-Dimensional Duplicate Data

Abstract: Cluster analysis is a fundamental method for studying big data problems, as it groups samples based on shared features. In cluster analysis, a particular class of big data problems is ...
Scientific Research Publishing

Miloud Aouidate, A. and Baba Ali, A.R. (2013) IDS False Alarm Reduction Using an Instance Selection KNN Memetic Algorithm. International Journal of Metaheuristics, 2, No. 4.

ABSTRACT: Cybersecurity has emerged as a global concern, amplified by the rapid expansion of IoT devices and the growing digitization of systems. In this context, traditional security solutions such ...
Frontiers

Network intrusion detection based on relative mutual K-nearest neighbor density peak clustering

1 Yibin University, School of Computer Science and Technology, Yibin, China 2 Southwest Petroleum University, School of Computer and Software, Chengdu, China Network security is the core guarantee for ...
GitHub

unsupervised-digit-clustering

This repository contains applied demonstrations of K-Nearest Neighbors (KNN) and K-Means Clustering, showcasing how these machine learning algorithms are used in classification, regression, and ...