Computational And Data Driven Chemistry Using Artificial Intelligence
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Computational And Data Driven Chemistry Using Artificial Intelligence
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Author : Takashiro Akitsu
language : en
Publisher: Elsevier
Release Date : 2021-10-08
Computational And Data Driven Chemistry Using Artificial Intelligence written by Takashiro Akitsu and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-08 with Science categories.
Computational and Data-Driven Chemistry Using Artificial Intelligence: Volume 1: Fundamentals, Methods and Applications highlights fundamental knowledge and current developments in the field, giving readers insight into how these tools can be harnessed to enhance their own work. Offering the ability to process large or complex data-sets, compare molecular characteristics and behaviors, and help researchers design or identify new structures, Artificial Intelligence (AI) holds huge potential to revolutionize the future of chemistry. Volume 1 explores the fundamental knowledge and current methods being used to apply AI across a whole host of chemistry applications. Drawing on the knowledge of its expert team of global contributors, the book offers fascinating insight into this rapidly developing field and serves as a great resource for all those interested in exploring the opportunities afforded by the intersection of chemistry and AI in their own work. Part 1 provides foundational information on AI in chemistry, with an introduction to the field and guidance on database usage and statistical analysis to help support newcomers to the field. Part 2 then goes on to discuss approaches currently used to address problems in broad areas such as computational and theoretical chemistry; materials, synthetic and medicinal chemistry; crystallography, analytical chemistry, and spectroscopy. Finally, potential future trends in the field are discussed. Provides an accessible introduction to the current state and future possibilities for AI in chemistry Explores how computational chemistry methods and approaches can both enhance and be enhanced by AI Highlights the interdisciplinary and broad applicability of AI tools across a wide range of chemistry fields
Machine Learning In Chemistry
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Author : Edward O. Pyzer-Knapp
language : en
Publisher:
Release Date : 2020-10-22
Machine Learning In Chemistry written by Edward O. Pyzer-Knapp and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-22 with Science categories.
Atomic-scale representation and statistical learning of tensorial properties -- Prediction of Mohs hardness with machine learning methods using compositional features -- High-dimensional neural network potentials for atomistic simulations -- Data-driven learning systems for chemical reaction prediction: an analysis of recent approaches -- Using machine learning to inform decisions in drug discovery : an industry perspective -- Cognitive materials discovery and onset of the 5th discovery paradigm.
Machine Learning And Data Driven Research In Chemistry
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Author : Hachmann
language : en
Publisher: Wiley-Blackwell
Release Date : 2017-12-08
Machine Learning And Data Driven Research In Chemistry written by Hachmann and has been published by Wiley-Blackwell this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-08 with categories.
Machine Learning And Pattern Recognition Methods In Chemistry From Multivariate And Data Driven Modeling
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Author : Jahan B. Ghasemi
language : en
Publisher: Elsevier
Release Date : 2022-10-20
Machine Learning And Pattern Recognition Methods In Chemistry From Multivariate And Data Driven Modeling written by Jahan B. Ghasemi and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-20 with Science categories.
Machine Learning and Pattern Recognition Methods in Chemistry from Multivariate and Data Driven Modeling outlines key knowledge in this area, combining critical introductory approaches with the latest advanced techniques. Beginning with an introduction of univariate and multivariate statistical analysis, the book then explores multivariate calibration and validation methods. Soft modeling in chemical data analysis, hyperspectral data analysis, and autoencoder applications in analytical chemistry are then discussed, providing useful examples of the techniques in chemistry applications. Drawing on the knowledge of a global team of researchers, this book will be a helpful guide for chemists interested in developing their skills in multivariate data and error analysis. Provides an introductory overview of statistical methods for the analysis and interpretation of chemical data Discusses the use of machine learning for recognizing patterns in multidimensional chemical data Identifies common sources of multivariate errors
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 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
Knowledge Based Expert Systems In Chemistry
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Author : Philip Judson
language : en
Publisher: Royal Society of Chemistry
Release Date : 2019-02-07
Knowledge Based Expert Systems In Chemistry written by Philip Judson 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 2019-02-07 with Chemistry categories.
There have been significant developments in the use of knowledge-based expert systems in chemistry since the first edition of this book was published in 2009. This new edition has been thoroughly revised and updated to reflect the advances. The underlying theme of the book is still the need for computer systems that work with uncertain or qualitative data to support decision-making based on reasoned judgements. With the continuing evolution of regulations for the assessment of chemical hazards, and changes in thinking about how scientific decisions should be made, that need is ever greater. Knowledge-based expert systems are well established in chemistry, especially in relation to toxicology, and they are used routinely to support regulatory submissions. The effectiveness and continued acceptance of computer prediction depends on our ability to assess the trustworthiness of predictions and the validity of the models on which they are based. Written by a pioneer in the field, this book provides an essential reference for anyone interested in the uses of artificial intelligence for decision making in chemistry. r in the field, this book provides an essential reference for anyone interested in the uses of artificial intelligence for decision making in chemistry.r in the field, this book provides an essential reference for anyone interested in the uses of artificial intelligence for decision making in chemistry.r in the field, this book provides an essential reference for anyone interested in the uses of artificial intelligence for decision making in chemistry.
Applications Of Artificial Intelligence In Process Systems Engineering
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Author : Jingzheng Ren
language : en
Publisher: Elsevier
Release Date : 2021-06-05
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 2021-06-05 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
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 Computers 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
Machine Learning And Hybrid Modelling For Reaction Engineering
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Author : Dongda Zhang
language : en
Publisher: Royal Society of Chemistry
Release Date : 2023-12-20
Machine Learning And Hybrid Modelling For Reaction Engineering written by Dongda Zhang 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 2023-12-20 with Science categories.