New research published in journals of the American Meteorological Society suggests that hurricane trends may become less predictable, discusses the limits of machine-learning weather forecasts, ...

As the core equipment in industrial production, rotating machinery bearings play a critical role. However, traditional feature extraction algorithms for vibration signals are susceptible to noise ...

Abstract: In recent years, High Entropy Alloys (HEAs) have gained significant interest due to their unique properties such as high strength, wear resistance, and high temperature stability. However, ...

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Graph neural networks for crystal property prediction typically require precise atomic ...

What is linear regression in machine learning ? Understanding Linear Regression in machine learning is considered as the basis or foundation in machine learning. In this video, we will learn what is ...

Machine learning (ML) is a subset of AI where a system learns patterns from data and makes decisions without being explicitly programmed for each outcome. In software development, this technology ...

Sample selection improves the efficiency and effectiveness of machine learning models by providing informative and representative samples. Typically, samples can be modeled as a sample graph, where ...

1 School of Earth Science and Engineering, Xi’an Shiyou University, Xi’an, China. 2 Key Laboratory of Petroleum Geology and Reservoir, Xi’an Shiyou University, Xi’an, China. In the course of oil and ...