With the predicted depletion of natural resources and alarming environmental issues,
sustainable development has become a popular as well as a much-needed concept in …

Graph convolutional neural networks (GNNs) have an excellent expression ability for
complex systems. However, the smoothing hypothesis based GNNs have certain limitations …

Accurate measurement of loader's working resistance is crucial for autonomous intelligence
and energy-saving optimization. This study highlights the limitations of strain sensors used …

The prevalence of microplastics (MPs) in global aquatic environments has received
considerable attention. Currently, concerns have been raised regarding reports that the …

In this paper, a filtering method is presented to estimate time-varying parameters of a missile
dual control system with tail fins and reaction jets as control variables. In this method, the …

Variational autoencoder has been widely used to build soft sensor models as a deep
unsupervised feature extractor in recent years. However, the vanilla VAE employs a single …

Soft sensors based on deep learning have been growing in industrial process applications,
inferring hard-to-measure but crucial quality-related variables. However, applications may …

The world is increasingly embracing cleaner and more sustainable energy sources, with
solar energy playing a crucial role in mitigating greenhouse gas emissions and addressing …

Visual sensation and perception refers to the process of sensing, organizing, identifying, and
interpreting visual information in environmental awareness and understanding …

Accurate modeling of critical quality variables is crucial for stable control and effective
optimization of the rotary kiln process. However, offline trained models often fail during …