Machine Learning Tools For Chemical Engineering
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Machine Learning Tools For Chemical Engineering
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Author : Francisco Javier López-Flores
language : en
Publisher: Elsevier
Release Date : 2025-05-15
Machine Learning Tools For Chemical Engineering written by Francisco Javier López-Flores and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-15 with Technology & Engineering categories.
Machine Learning Tools for Chemical Engineering: Methodologies and Applications examines how machine learning (ML) techniques are applied in the field, offering precise, fast, and flexible solutions to address specific challenges.ML techniques and methodologies offer significant advantages (such as accuracy, speed of execution, and flexibility) over traditional modeling and optimization techniques. This book integrates ML techniques to solve problems inherent to chemical engineering, providing practical tools and a theoretical framework combining knowledge modeling, representation, and management, tailored to the chemical engineering field. It provides a precedent for applied Al, but one that goes beyond purely data-centric ML. It is firmly grounded in the philosophies of knowledge modeling, knowledge representation, search and inference, and knowledge extraction and management.Aimed at graduate students, researchers, educators, and industry professionals, this book is an essential resource for those seeking to implement ML in chemical processes, aiming to foster optimization and innovation in the sector. - Outlines the current and potential future contribution of machine learning, the use of data science, and, ultimately, how to correctly use machine learning tools specifically in chemical engineering• Devoted to the correct application and interpretation of the results in various phases of the development of decision support systems: data collection, model development, training, and testing, as well as application in chemical engineering• Examines chemical engineering-specific challenges and problems, including noise, manufacturing equipment, and domain-specific solutions, such as physical knowledge using relevant case study examples
Machine Learning In Chemistry
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Author : Jon Paul Janet
language : en
Publisher: American Chemical Society
Release Date : 2020-05-28
Machine Learning In Chemistry written by Jon Paul Janet and has been published by American Chemical Society this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-28 with Science categories.
Recent advances in machine learning or artificial intelligence for vision and natural language processing that have enabled the development of new technologies such as personal assistants or self-driving cars have brought machine learning and artificial intelligence to the forefront of popular culture. The accumulation of these algorithmic advances along with the increasing availability of large data sets and readily available high performance computing has played an important role in bringing machine learning applications to such a wide range of disciplines. Given the emphasis in the chemical sciences on the relationship between structure and function, whether in biochemistry or in materials chemistry, adoption of machine learning by chemistsderivations where they are important
Applications Of Artificial Intelligence In Process Systems Engineering
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Author : Jingzheng Ren
language : en
Publisher: Elsevier
Release Date : 2021-06-17
Applications Of Artificial Intelligence In Process Systems Engineering written by Jingzheng Ren and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-17 with Technology & Engineering categories.
Applications of Artificial Intelligence in Process Systems Engineering offers a broad perspective on the issues related to artificial intelligence technologies and their applications in chemical and process engineering. The book comprehensively introduces the methodology and applications of AI technologies in process systems engineering, making it an indispensable reference for researchers and students. As chemical processes and systems are usually non-linear and complex, thus making it challenging to apply AI methods and technologies, this book is an ideal resource on emerging areas such as cloud computing, big data, the industrial Internet of Things and deep learning. With process systems engineering's potential to become one of the driving forces for the development of AI technologies, this book covers all the right bases. Explains the concept of machine learning, deep learning and state-of-the-art intelligent algorithms Discusses AI-based applications in process modeling and simulation, process integration and optimization, process control, and fault detection and diagnosis Gives direction to future development trends of AI technologies in chemical and process engineering
Machine Learning In Chemistry
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Author : Hugh M. Cartwright
language : en
Publisher: Royal Society of Chemistry
Release Date : 2020-07-15
Machine Learning In Chemistry written by Hugh M. Cartwright and has been published by Royal Society of Chemistry this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-15 with Science categories.
Progress in the application of machine learning (ML) to the physical and life sciences has been rapid. A decade ago, the method was mainly of interest to those in computer science departments, but more recently ML tools have been developed that show significant potential across wide areas of science. There is a growing consensus that ML software, and related areas of artificial intelligence, may, in due course, become as fundamental to scientific research as computers themselves. Yet a perception remains that ML is obscure or esoteric, that only computer scientists can really understand it, and that few meaningful applications in scientific research exist. This book challenges that view. With contributions from leading research groups, it presents in-depth examples to illustrate how ML can be applied to real chemical problems. Through these examples, the reader can both gain a feel for what ML can and cannot (so far) achieve, and also identify characteristics that might make a problem in physical science amenable to a ML approach. This text is a valuable resource for scientists who are intrigued by the power of machine learning and want to learn more about how it can be applied in their own field.
Machine Learning And Data Science In The Oil And Gas Industry
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Author : Patrick Bangert
language : en
Publisher: Gulf Professional Publishing
Release Date : 2021-03-04
Machine Learning And Data Science In The Oil And Gas Industry written by Patrick Bangert and has been published by Gulf Professional Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-04 with Science categories.
Machine Learning and Data Science in the Oil and Gas Industry explains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas operations, and how to manage the data stream moving forward. Practical in its approach, the book explains all aspects of a data science or machine learning project, including the managerial parts of it that are so often the cause for failure. Several real-life case studies round out the book with topics such as predictive maintenance, soft sensing, and forecasting. Viewed as a guide book, this manual will lead a practitioner through the journey of a data science project in the oil and gas industry circumventing the pitfalls and articulating the business value. - Chart an overview of the techniques and tools of machine learning including all the non-technological aspects necessary to be successful - Gain practical understanding of machine learning used in oil and gas operations through contributed case studies - Learn change management skills that will help gain confidence in pursuing the technology - Understand the workflow of a full-scale project and where machine learning benefits (and where it does not)
Coulson And Richardson S Chemical Engineering
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Author : Ajay Kumar Ray
language : en
Publisher: Butterworth-Heinemann
Release Date : 2023-06-30
Coulson And Richardson S Chemical Engineering written by Ajay Kumar Ray and has been published by Butterworth-Heinemann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-30 with Technology & Engineering categories.
Coulson and Richardson's Chemical Engineering: Volume 2B, Separation Processes, Sixth Edition, covers distillation and gas absorption, illustrating applications of the fundamental principles of mass transfer. Several techniques, including adsorption, ion exchange, chromatographic membrane separations and process intensification are comprehensively covered and explored. - Presents content converted from textbooks into fully revised reference material - Provides content that ranges from foundational to technical - Includes new additions, such as emerging applications, numerical methods, and computational tools
Ai In Chemical Engineering
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Author : José A. Romagnoli
language : en
Publisher: CRC Press
Release Date : 2024-12-31
Ai In Chemical Engineering written by José A. Romagnoli and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-31 with Computers categories.
Industry 4.0 is revolutionizing chemical manufacturing. Today's chemical companies are swiftly embracing the digital era, recognizing the significant benefits of interconnected products, production equipment, and personnel. As technology advances and production volumes grow, there is an increasing need for new computational tools and innovative solutions to address everyday challenges. AI in Chemical Engineering: Unlocking the Power Within Data introduces readers to the essential concepts of machine learning and their application in the chemical and process industries, aiming to enhance efficiency, adaptability, and profitability. This work delves into the transformation of traditional plant operations into integrated and intelligent systems, providing readers with a foundation for developing and understanding the tools necessary for data collection and analysis, thereby gaining valuable insights and practical applications. Introduces the principles and applications of unsupervised learning and discusses the role of machine learning in extracting information from plant data and transforming it into knowledge Conveys the concepts, principles, and applications of supervised learning, setting the stage for developing advanced monitoring systems, complex predictive models, and advanced computer vision applications Explores implementation of reinforced learning ideas for chemical process control and optimization, investigating various model structures and discussing their practical implementation in both simulation and experimental units Incorporates sample code examples in Python to illustrate key concepts Includes real-life case studies in the context of chemical engineering and covers a wide variety of chemical engineering applications from oil and gas to bioengineering and electrochemistry Clearly defines types of problems in chemical engineering subject to AI solutions and relates them to subfields of AI This practical text, designed for advanced chemical engineering students and industry practitioners, introduces concepts and theories in a logical and sequential manner. It serves as an essential resource, helping readers understand both current and emerging developments in this important and evolving field.
Machine Learning And Artificial Intelligence In Chemical And Biological Sensing
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Author : Jeong-Yeol Yoon
language : en
Publisher: Elsevier
Release Date : 2024-07-07
Machine Learning And Artificial Intelligence In Chemical And Biological Sensing written by Jeong-Yeol Yoon and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-07 with Science categories.
Machine learning (ML) has recently become popular in chemical and biological sensing applications. ML is a subset of artificial intelligence (AI) and other AI techniques have been used in various chemical and biological sensing. Machine Learning and Artificial Intelligence in Chemical and Biological Sensing covers the theoretical background and practical applications of various ML/AI methods toward chemical and biological sensing. No comprehensive reference text has been available previously to cover the wide breadth of this topic. The Editors have written the first three chapters to firmly introduce the reader to fundamental ML theories that can be used for chemical/biosensing. The subsequent chapters then cover the practical applications with contributions by various experts in the field. They show how ML and AI-based techniques can provide solutions for: 1) identifying and quantifying target molecules when specific receptors are unavailable 2) analyzing complex mixtures of target molecules, such as gut microbiome and soil microbiome3) analyzing high-throughput and high-dimensional data, such as drug screening, molecular interaction, and environmental toxicant analysis, 4) analyzing complex data sets where fingerprinting approach is needed This book is written primarily for upper undergraduate students, graduate students, research staff, and faculty members at teaching and research universities and colleges who are working on chemical sensing, biosensing, analytical chemistry, analytical biochemistry, biomedical imaging, medical diagnostics, environmental monitoring, and agricultural applications. - Presents the first comprehensive reference text on the use of ML and AI for chemical and biological sensing - Provides a firm grounding in the fundamental theories on ML and AI before covering the practical applications with contributions by various experts in the field - Includes a wide array of practical applications covered, including: E-nose, Raman, SERS, lens-free imaging, multi/hyperspectral imaging, NIR/optical imaging, receptor-free biosensing, paper microfluidics, single molecule analysis in biomedicine, in situ protein characterization, microbial population dynamics, and all-in-one sensor systems
Artificial Intelligence In Chemical Engineering
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Author : Thomas E. Quantrille
language : en
Publisher: Elsevier
Release Date : 2012-12-02
Artificial Intelligence In Chemical Engineering written by Thomas E. Quantrille and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-02 with Technology & Engineering categories.
Artificial intelligence (AI) is the part of computer science concerned with designing intelligent computer systems (systems that exhibit characteristics we associate with intelligence in human behavior). This book is the first published textbook of AI in chemical engineering, and provides broad and in-depth coverage of AI programming, AI principles, expert systems, and neural networks in chemical engineering. This book introduces the computational means and methodologies that are used to enable computers to perform intelligent engineering tasks. A key goal is to move beyond the principles of AI into its applications in chemical engineering. After reading this book, a chemical engineer will have a firm grounding in AI, know what chemical engineering applications of AI exist today, and understand the current challenges facing AI in engineering. - Allows the reader to learn AI quickly using inexpensive personal computers - Contains a large number of illustrative examples, simple exercises, and complex practice problems and solutions - Includes a computer diskette for an illustrated case study - Demonstrates an expert system for separation synthesis (EXSEP) - Presents a detailed review of published literature on expert systems and neural networks in chemical engineering
30th European Symposium On Computer Aided Chemical Engineering
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Author : Sauro Pierucci
language : en
Publisher: Elsevier
Release Date : 2020-10-23
30th European Symposium On Computer Aided Chemical Engineering written by Sauro Pierucci and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-23 with Technology & Engineering categories.
30th European Symposium on Computer Aided Chemical Engineering, Volume 47 contains the papers presented at the 30th European Symposium of Computer Aided Process Engineering (ESCAPE) event held in Milan, Italy, May 24-27, 2020. It is a valuable resource for chemical engineers, chemical process engineers, researchers in industry and academia, students, and consultants for chemical industries. - Presents findings and discussions from the 30th European Symposium of Computer Aided Process Engineering (ESCAPE) event - Offers a valuable resource for chemical engineers, chemical process engineers, researchers in industry and academia, students, and consultants for chemical industries