IEEE

A Transformer-Based Industrial Time Series Prediction Model With Multivariate Dynamic Embedding

Abstract: Industrial time series prediction (ITSP) is critical to the predictive maintenance system of modern industry. However, time-varying conditions and complex industrial processes cause the ...
Frontiers

Improving Parameters estimation of a truncated Poisson regression model based on meta-heuristic optimization algorithms

The final, formatted version of the article will be published soon. {The paper discusses computational and numerical challenges that are associated with the truncation of the information and which ...
IEEE

A Survey on Multivariate Time Series Imputation Using Adversarial Learning

Abstract: Multivariate time series (MTS) are captured in a great variety of real-world applications. However, analysing and modeling the data for classification and forecasting purposes can become ...
GitHub

Model-Based Clustering and Variable Selection for Multivariate Count Data

Model-based clustering provides a principled way of developing clustering methods. We develop a new model-based clustering methods for count data. The method combines clustering and variable selection ...
Frontiers

Development and comparison of multivariate diagnostic models for rapidly progressive central precocious puberty in girls: the role of serum osteocalcin

Objectives: To develop a diagnostic prediction model for rapidly progressive central precocious puberty (RP-CPP) and evaluate the contribution of osteocalcin(OC) to the model. Methods: For a total of ...