1 School of Artificial Intelligence and Information Engineering, Zhejiang University of Science and Technology, Hangzhou, China. 2 School of Sciences, Zhejiang University of Science and Technology, ...

Quadratic regression extends linear regression by adding squared terms and pairwise interaction terms, enabling the model to capture non-linear structure and predictor interactions. The article ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...

bDepartment of Computer Information Science, State Key Laboratory of Internet of Things for Smart City, University of Macau, Macau, China cSchool of Chinese Medicine, Li Ka Shing Faculty of Medicine, ...

FSML (Fortran Statistics and Machine Learning) is a scientific toolkit consisting of common statistical and machine learning procedures, including basic statistics (e.g., mean, variance, correlation), ...

Rocks and their structures require careful planning to prevent loss of life and economic damage from human error. In civil engineering, mining, cave mining, tunneling ...

Simo Särkkä and Arno Solin (2019). Applied Stochastic Differential Equations. Cambridge University Press. Cambridge, UK. The book can be ordered through Cambridge University Press or, e.g., from ...

Non-linear regression modeling is common in epidemiology for prediction purposes or estimating relationships between predictor and response variables. Restricted cubic spline (RCS) regression is one ...

Whether you’re passing secret notes in class or downloading images from a space probe, Reed-Solomon codes offer an ingenious way to embed information and correct for errors. Space exploration requires ...

System identification learns models of dynamical systems from input–output measurements. Estimated models should generalize by predicting system’s output responses to new, previously unseen inputs.

Geothermal heat flow (GHF) data measured directly from boreholes are sparse. Purely physics-based models for geothermal heat flow prediction require various simplifications and are feasible only for ...