Applied AI Techniques in the Process Industry: From Molecular Design to Process Design and Optimization

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Applied AI Techniques in the Process Industry: From Molecular Design to Process Design and Optimization

Chang He - Nama Orang; Jingzheng Ren - Nama Orang;

Applied AI Techniques in the Process Industry identifies and categorizes the various hybrid models available that integrate data-driven models for energy-relevant systems and processes with different forms of process knowledge and domain expertise. State-of-the-art techniques such as reduced-order modeling, sparse identification, and physics-informed neural networks are comprehensively summarized, along with their benefits, such as improved interpretability and predictive power.

Numerous in-depth case studies regarding the covered models and methods for data-driven modeling, process optimization, and machine learning are presented, from screening high-performance ionic liquids and AI-assisted drug design to designing heat exchangers with physics-informed deep learning.

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Judul Seri: -
No. Panggil: -
Penerbit: Germany : Wiley., 2025
Deskripsi Fisik: -
Bahasa: English
ISBN/ISSN: 978-3-527-84549-1
Klasifikasi: NONE
Tipe Isi: text
Tipe Media: -
Tipe Pembawa: volume
Edisi: -
Subjek: Artificial Intelligence - Process Industry
Molecular Design and Chemistry
Industrial Technology and Innovation
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Pernyataan Tanggungjawab: -

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