EurekAlert!

Accelerated streaming subgraph matching framework is faster, more robust, and scalable

Graphs are widely used to represent complex relationships in everyday applications such as social networks, bioinformatics, ...
SciELO

Machine learning classification based on k-Nearest Neighbors for PolSAR data

In this work, we focus on obtaining insights of the performances of some well-known machine learning image classification techniques (k-NN, Support Vector Machine, randomized decision tree and one ...
Lexington Herald Leader

Could bankruptcy be in the works for a potentially insolvent whiskey start-up?

Federal judge ordered receivership for Uncle Nearest after $100M loan default. Farm Credit alleges asset discrepancies while Weaver family rejects bankruptcy. Company seeks new investors to acquire ...
IEEE

K-Nearest Neighbor Algorithm Based on the Framework of Ordered Pair of Normalized Real Numbers

Abstract: The K-Nearest Neighbors (kNN) algorithm, a cornerstone of supervised learning, relies on similarity measures constrained by real-number-based distance metrics. A critical limitation of ...
Frontiers

Fault diagnosis algorithm based on multi-channel neighbor feature convolutional network

Introduction: The health status of bearings is an essential prerequisite to ensure the safe and stable operation of vehicles. However, the negative impact of covariate shifts among data channels on ...
Scientific Research Publishing

Tang, Y., Chang, Y. and Li, K. (2023) Applications of K-Nearest Neighbor Algorithm in Intelligent Diagnosis of Wind Turbine Blades Damage. Renewable Energy, 212, 855-864.

ABSTRACT: To ensure the efficient operation and timely maintenance of wind turbines, thereby enhancing energy security, it is critical to monitor the operational status of wind turbines and promptly ...
Visual Studio Magazine

Implementing k-NN Classification Using C#

Dr. James McCaffrey of Microsoft Research presents a full demo of k-nearest neighbors classification on mixed numeric and categorical data. Compared to other classification techniques, k-NN is easy to ...
IEEE

An adaptive k-nearest neighbor algorithm

Abstract: An adaptive k-nearest neighbor algorithm (AdaNN) is brought forward in this paper to overcome the limitation of the traditional k-nearest neighbor algorithm (kNN) which usually identifies ...