Abstract: The insulated gate bipolar transistor (IGBT), one of the most vulnerable component, is one of the most precious central component in the converter interior. High junction temperature will ...

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...

This paper deals with the use of multiple linear regression to predict the viscosity of engine oil at 100 °C based on the analysis of selected parameters obtained by Fourier transform infrared ...

1 Tianjin Engineering Research Center of Civil Aviation Energy Environment and Green Development, Civil Aviation University of China, Tianjin, China. 2 Groupe d’Acoustigue de l’ Université de ...

Post-stack seismic inversion techniques encompass a range of procedures used to invert stacked seismic data into quantitative rock physics parameters 1. Typically, this inversion, which utilizes ...

Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...

When you visit a hospital, artificial intelligence (AI) models can assist doctors by analysing medical images or predicting patient outcomes based on historical data. If you apply for a job, AI ...

Machine learning (ML) algorithms are at the core of many modern technologies, from recommendation systems to self-driving cars. One of the key factors that determine the efficiency and scalability of ...

In the rapidly evolving landscape of business analytics, machine learning algorithms have become indispensable tools for extracting insights, making predictions, and automating decision-making ...

Dr. James McCaffrey of Microsoft Research says the technique is easy to tune, works well with small datasets and produces highly interpretable predictions, but there are also trade-off cons. The goal ...

Machine learning and deep learning have been widely embraced, and even more widely misunderstood. In this article, I’ll step back and explain both machine learning and deep learning in basic terms, ...