Artificial Intelligence in Chemical Engineering
Algorithms, Models and Applications
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Beschreibung
Artificial Intelligence in Chemical Engineering focuses on a comprehensive and understanding exploration of the integration of artificial intelligence (AI) into various aspects of chemical engineering. The book kicks off with a comprehensive introduction that covers the background, present situation, and future of artificial intelligence applications, as well as the opportunities and challenges. The book then comprehensively addresses the fundamental principles of artificial intelligence (AI) and machine learning. Readers gain a comprehensive understanding of fundamental AI concepts, machine learning algorithms, and the critical model training and validation procedures. The book then discusses AI model data acquisition and preprocessing, including data collection, quality assurance, and feature engineering and selection. The following chapters are structured to encompass a broad range of AI applications in the field of chemical engineering, such as process modeling, analysis, optimization, control, reaction engineering, safety, etc. The wide-ranging influence of AI on many domains within chemical engineering is demonstrated by its interdisciplinary applications in areas such as chemical sciences, advanced process monitoring, predictive maintenance, materials science, supply chain management, and human-AI collaboration. This book is a valuable resource for researchers, engineers, and students who want to explore the dynamic interface of artificial intelligence and chemical engineering.
Autor*in
Seckin Karagoz
Themen in »Artificial Intelligence in Chemical Engineering«
Mehrskalige Modellierung und Simulation Datenerfassung und Merkmalsbildung Prädiktive Modellierung und Prozessoptimierung Steuerungssysteme und Entscheidungsunterstützung Multiscale Modeling-Simulation Data Acquisition and Featurization Predictive Modelling and Process Optimization Control Systems and Decision Support Sustainable Process Development and Intensification Process Safety and Risk Management.