Results 211 to 220 of about 38,896 (265)

A Graph‐Based Generative Artificial Intelligence Methodology for Autocorrection of Utility‐System P&IDs

open access: yesChemie Ingenieur Technik, EarlyView.
This work explores generative AI for automated revision of Piping and Instrumentation Diagrams (P&IDs). We frame P&ID correction as a translation problem, converting attributed P&ID graphs into sequences and learning revisions with a transformer‐based model.
Lukas Schulze Balhorn   +5 more
wiley   +1 more source

Data‐driven simulation of crude distillation using Aspen HYSYS and comparative machine learning models

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
Integrated Aspen HYSYS–machine learning framework for predicting product yields and quality variables. Abstract Crude oil refining is a complex process requiring precise modelling to optimize yield, quality, and efficiency. This study integrates Aspen HYSYS® simulations with machine learning techniques to develop predictive models for key refinery ...
Aldimiro Paixão Domingos   +3 more
wiley   +1 more source

Application of improved graph convolutional network for cortical surface parcellation. [PDF]

open access: yesSci Rep
Tan J   +10 more
europepmc   +1 more source

Artificial intelligence in enzyme catalysis: Emerging trends and applications in biocatalyst engineering

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
Schematic representation of artificial intelligence approaches in enzyme catalysis, integrating bibliometric analysis, emerging research trends, and machine learning tools for enzyme design, prediction, and industrial biocatalytic applications. Abstract This study systematically explores the applications of artificial intelligence (AI) in enzyme ...
Misael Bessa Sales   +6 more
wiley   +1 more source

Orchestrating Green Transformation: How AI Adoption Enables Corporate Carbon Neutrality

open access: yesCorporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT As carbon neutrality has become a central goal of global climate governance, how firms achieve low‐carbon transformation has emerged as a critical research issue. However, prior studies have primarily focused on macro‐ or industry‐level analyses, offering limited and fragmented insights into how digital technologies—particularly AI—affect firm‐
Xiaonan Dong, Sungjin Son
wiley   +1 more source

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