We demonstrate how to design and apply domain-specific modifications to convolutional
neural networks (CNNs) to improve model performance on hyperspectral images of grain …

The sediment transport, involving the movement of the bedload and suspended sediment in
the basins, is a critical environmental concern that worsens water scarcity and leads to …

Oil refining industry has been using processes to convert heavy oil into high-value materials
due to environmental regulations and decreasing demand for heavy oil. Atmospheric …

To promote the updating and iteration of the construction field, the construction knowledge
graph can expand the professional knowledge system within the field and provide scientific …

Accurate acid-base treatment prediction is necessary to achieve the required yield, given the
inherent complexity, high nonlinearity, and restricted availability of data samples; to address …

In this study, an inverse design framework was constructed to explore gradient honeycomb
structures (HCS) with high impact resistance. By establishing the relationship between the …

Fault detection and diagnosis (FDD) is an essential tool to ensure safety in chemical
industries, and nowadays, many reconstruction-based deep learning methods are active in …

Background Operation designs on rapid developed advanced chemical processes require
proper models and parameter identification of these models needs input-output data sets …

The accuracy of rolling force prediction is key to improving the precision of strip thickness
control. The compressive load required for the strip in the rolling process is not only related …

We review the utility and application of artificial intelligence (AI) and machine learning (ML)
at various process scales in this work, from molecules and reactions to materials to …