IEEE

Attention-Guided Position-Sensitive Multiple Imputation for Wastewater Treatment Process

Abstract: Missing values frequently appearing in the wastewater treatment process are automatically replaced by zero to ensure the implementation of downstream applications. These meaningless zero ...
Scientific Research Publishing

KAN-Transformer Fusion with Mixture of Experts for Temporal Imputation of Spatiotemporal Air Pollution Data ()

The Kolmogorov-Arnold Network (abbr. KAN) is a novel neural network architecture inspired by the Kolmogorov-Arnold ...
Frontiers

AI-Driven Spatiotemporal Data Mining: Novel Architectures for Imputation and Forecasting

Accurate spatiotemporal prediction is fundamentally essential for anticipating and managing the dynamic evolutions within global physical, environmental, ...
IEEE

Conditional Time Series Diffusion Model for High-Speed Train Multi-Sensor Signals Imputation

Abstract: Sensors are widely deployed on high-speed trains for real-time operational status monitoring. The integrity of multi-sensor signals over time is critical for the train’s Prognostics and ...
SciELO

Data variability in the imputation quality of missing data

Imputation methods were developed to define estimates for missing data and hence solve possible problems generated by the loss of this information. This study aims to assess whether data variability ...