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Computational And Data Driven Chemistry Using Artificial Intelligence

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Computational and Data Driven Chemistry Using Artificial Intelligence

Computational and Data Driven Chemistry Using Artificial Intelligence Book
Author : Takashiro Akitsu
Publisher : Elsevier
Release : 2021-06-15
ISBN : 9780128222492
Language : En, Es, Fr & De

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Book Description :

Offering the ability to process large or complex data-sets, compare molecular characteristics and behaviours, and help researchers design or identify new structures, Artificial Intelligence (AI) holds huge potential to revolutionise the future of chemistry. 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. Volume 1 explores the fundamental knowledge and current methods being used to apply AI across a whole host of chemistry applications. 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. Drawing on the knowledge of its expert team of global contributors, Computational and Data-Driven Chemistry Using Artificial Intelligence: Volume 1: Fundamentals, Methods and Applications is a fascinating insight into this rapidly developing field and a great resource for all those interested in exploring the opportunities afforded by the intersection of chemistry and AI in their own work. 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, broad applicability of AI tools across a wide range of chemistry fields

Applications of Computational Intelligence in Data Driven Trading

Applications of Computational Intelligence in Data Driven Trading Book
Author : Cris Doloc
Publisher : John Wiley & Sons
Release : 2019-10-29
ISBN : 1119550505
Language : En, Es, Fr & De

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Book Description :

“Life on earth is filled with many mysteries, but perhaps the most challenging of these is the nature of Intelligence.” – Prof. Terrence J. Sejnowski, Computational Neurobiologist The main objective of this book is to create awareness about both the promises and the formidable challenges that the era of Data-Driven Decision-Making and Machine Learning are confronted with, and especially about how these new developments may influence the future of the financial industry. The subject of Financial Machine Learning has attracted a lot of interest recently, specifically because it represents one of the most challenging problem spaces for the applicability of Machine Learning. The author has used a novel approach to introduce the reader to this topic: The first half of the book is a readable and coherent introduction to two modern topics that are not generally considered together: the data-driven paradigm and Computational Intelligence. The second half of the book illustrates a set of Case Studies that are contemporarily relevant to quantitative trading practitioners who are dealing with problems such as trade execution optimization, price dynamics forecast, portfolio management, market making, derivatives valuation, risk, and compliance. The main purpose of this book is pedagogical in nature, and it is specifically aimed at defining an adequate level of engineering and scientific clarity when it comes to the usage of the term “Artificial Intelligence,” especially as it relates to the financial industry. The message conveyed by this book is one of confidence in the possibilities offered by this new era of Data-Intensive Computation. This message is not grounded on the current hype surrounding the latest technologies, but on a deep analysis of their effectiveness and also on the author’s two decades of professional experience as a technologist, quant and academic.

Artificial Intelligence in Drug Discovery

Artificial Intelligence in Drug Discovery Book
Author : Nathan Brown
Publisher : Royal Society of Chemistry
Release : 2020-11-11
ISBN : 1839160543
Language : En, Es, Fr & De

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Book Description :

Following significant advances in deep learning and related areas interest in artificial intelligence (AI) has rapidly grown. In particular, the application of AI in drug discovery provides an opportunity to tackle challenges that previously have been difficult to solve, such as predicting properties, designing molecules and optimising synthetic routes. Artificial Intelligence in Drug Discovery aims to introduce the reader to AI and machine learning tools and techniques, and to outline specific challenges including designing new molecular structures, synthesis planning and simulation. Providing a wealth of information from leading experts in the field this book is ideal for students, postgraduates and established researchers in both industry and academia.

Green Chemical Engineering

Green Chemical Engineering Book
Author : S. Suresh,S. Sundaramoorthy
Publisher : CRC Press
Release : 2014-12-18
ISBN : 1466558857
Language : En, Es, Fr & De

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Book Description :

While chemical products are useful in their own right—they address the demands and needs of the masses—they also drain our natural resources and generate unwanted pollution. Green Chemical Engineering: An Introduction to Catalysis, Kinetics, and Chemical Processes encourages minimized use of non-renewable natural resources and fosters maximized pollution prevention. This text stresses the importance of developing processes that are environmentally friendly and incorporate the role of green chemistry and reaction engineering in designing these processes. Focused on practical application rather than theory, the book integrates chemical reaction engineering and green chemical engineering, and is divided into two sections. The first half of the book covers the basic principles of chemical reaction engineering and reactor design, while the second half of the book explores topics on green reactors, green catalysis, and green processes. The authors mix in elaborate illustrations along with important developments, practical applications, and recent case studies. They also include numerous exercises, examples, and problems covering the various concepts of reaction engineering addressed in this book, and provide MATLAB® software used for developing computer codes and solving a number of reaction engineering problems. Consisting of six chapters organized into two sections, this text: Covers the basic principles of chemical kinetics and catalysis Gives a brief introduction to classification and the various types of chemical reactors Discusses in detail the differential and integral methods of analysis of rate equations for different types of reactions Presents the development of rate equations for solid catalyzed reactions and enzyme catalyzed biochemical reactions Explains methods for estimation of kinetic parameters from batch reactor data Details topics on homogeneous reactors Includes graphical procedures for the design of multiple reactors Contains topics on heterogeneous reactors including catalytic and non-catalytic reactors Reviews various models for non-catalytic gas–solid and gas–liquid reactions Introduces global rate equations and explicit design equations for a variety of non-catalytic reactors Gives an overview of novel green reactors and the application of CFD technique in the modeling of green reactors Offers detailed discussions of a number of novel reactors Provides a brief introduction to CFD and the application of CFD Highlights the development of a green catalytic process and the application of a green catalyst in the treatment of industrial effluent Comprehensive and thorough in its coverage, Green Chemical Engineering: An Introduction to Catalysis, Kinetics, and Chemical Processes explains the basic concepts of green engineering and reactor design fundamentals, and provides key knowledge for students at technical universities and professionals already working in the industry.

New Challenges in Applied Intelligence Technologies

New Challenges in Applied Intelligence Technologies Book
Author : Radoslaw Katarzyniak
Publisher : Springer Science & Business Media
Release : 2008-05-29
ISBN : 3540793542
Language : En, Es, Fr & De

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Book Description :

To built intelligent systems that can cope with real world problems we need to - velop computational mechanisms able to deal with very large amounts of data, gen- ate complex plans, schedules, and resource allocation strategies, re-plan their actions in real time, provide user friendly communication for human-device interactions, and perform complex optimization problems. In each of these tasks intelligence techno- gies play an important role, providing designers and creators with effective and adequate computational models. The field of intelligence technologies covers a variety of computational approaches that are often suggested and inspired by biological systems, exhibiting functional richness and flexibility of their natural behavior. This class of technologies consists of such important approaches as data mining algorithms, neural networks, genetic al- rithms, fuzzy and multi-valued logics, rough sets, agent-oriented computation, often integrated into complex hybrid solutions. Intelligence technologies are used to built machines that can act and think like living systems, solve problems in an autonomous way, develop rich private knowledge bases and produce results not foreseen and programmed in a direct way by designers and creators.

Modeling Design and Optimization of Multiphase Systems in Minerals Processing

Modeling  Design and Optimization of Multiphase Systems in Minerals Processing Book
Author : Luis A. Cisternas
Publisher : MDPI
Release : 2020-03-19
ISBN : 3039284002
Language : En, Es, Fr & De

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Book Description :

Mineral processing deals with complex particle systems with two-, three- and more phases. The modeling and understanding of these systems are a challenge for research groups and a need for the industrial sector. This Special Issue aims to present new advances, methodologies, applications, and case studies of computer-aided analysis applied to multiphase systems in mineral processing. This includes aspects such as modeling, design, operation, optimization, uncertainty analysis, among other topics. The special issue contains a review article and eleven articles that cover different methodologies of modeling, design, optimization, and analysis in problems of adsorption, leaching, flotation, and magnetic separation, among others. Consequently, the topics covered are of interest to readers from academia and industry.

Surface Chemistry with Machine Learning and Quantum Mechanics

Surface Chemistry with Machine Learning and Quantum Mechanics Book
Author : Venkatesh Botu
Publisher :
Release : 2016
ISBN :
Language : En, Es, Fr & De

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Book Description :

Surface chemistry is a phenomenon manifesting itself in several key areas; catalysis, materials fabrication, and emissions mitigation, to name a few. At the present time, atomistic computational driven efforts to study such processes are dominated by models based on quantum mechanics. Their flexibility in studying diverse chemistries, along with the ability to predict accurate thermodynamic and kinetic insights of surface processes, makes them increasingly popular. From ultra-low temperature and pressure to normal operating conditions these methods are now commonly utilized. Nevertheless, the computational burden inherent in the method renders it insufficient to keep up with the current need for quick discovery, i.e. predicting properties of millions of permutations of materials or the meticulous analysis of a chemical reaction on a material. Consequently, a push to go beyond traditional design and characterization practices to explain materials chemistry is becoming necessary. In this thesis, a new framework that combines quantum mechanics with data-driven machine learning methods is put forth. The premise of such an approach is to mine and find patterns within data and in doing so come up with human fathomable relationships, to help accelerate discovery. Here, I focus on model development, which begins by generating data, identifying descriptors for a process, learning from the data and culminating with model validation. This then enables accelerated estimation of thermodynamic and kinetic properties of surface processes. Two detailed examples of this hybrid approach are discussed; (i) a guided and targeted catalyst design framework to identify optimal dopants to enhance thermochemical dissociation of H2O, and (ii) a force predictive framework (commonly known as force field) to rapidly compute forces on atoms, so as to extend dynamic simulations to length and time scales beyond current quantum mechanical methods.

Soft Computing in Water Resources Engineering

Soft Computing in Water Resources Engineering Book
Author : G. Tayfur
Publisher : WIT Press
Release : 2014-11-02
ISBN : 1845646363
Language : En, Es, Fr & De

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Book Description :

Engineers have attempted to solve water resources engineering problems with the help of empirical, regression-based and numerical models. Empirical models are not universal, nor are regression-based models. The numerical models are, on the other hand, physics-based but require substantial data measurement and parameter estimation. Hence, there is a need to employ models that are robust, user-friendly, and practical and that do not have the shortcomings of the existing methods. Artificial intelligence methods meet this need. Soft Computing in Water Resources Engineering introduces the basics of artificial neural networks (ANN), fuzzy logic (FL) and genetic algorithms (GA). It gives details on the feed forward back propagation algorithm and also introduces neuro-fuzzy modelling to readers. Artificial intelligence method applications covered in the book include predicting and forecasting floods, predicting suspended sediment, predicting event-based flow hydrographs and sedimentographs, locating seepage path in an earth-fill dam body, and the predicting dispersion coefficient in natural channels. The author also provides an analysis comparing the artificial intelligence models and contemporary non-artificial intelligence methods (empirical, numerical, regression, etc.). The ANN, FL, and GA are fairly new methods in water resources engineering. The first publications appeared in the early 1990s and quite a few studies followed in the early 2000s. Although these methods are currently widely known in journal publications, they are still very new for many scientific readers and they are totally new for students, especially undergraduates. Numerical methods were first taught at the graduate level but are now taught at the undergraduate level. There are already a few graduate courses developed on AI methods in engineering and included in the graduate curriculum of some universities. It is expected that these courses, too, will soon be taught at the undergraduate levels.

Artificial Neural Networks in Biological and Environmental Analysis

Artificial Neural Networks in Biological and Environmental Analysis Book
Author : Grady Hanrahan
Publisher : CRC Press
Release : 2011-01-18
ISBN : 9781439812594
Language : En, Es, Fr & De

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Book Description :

Originating from models of biological neural systems, artificial neural networks (ANN) are the cornerstones of artificial intelligence research. Catalyzed by the upsurge in computational power and availability, and made widely accessible with the co-evolution of software, algorithms, and methodologies, artificial neural networks have had a profound impact in the elucidation of complex biological, chemical, and environmental processes. Artificial Neural Networks in Biological and Environmental Analysis provides an in-depth and timely perspective on the fundamental, technological, and applied aspects of computational neural networks. Presenting the basic principles of neural networks together with applications in the field, the book stimulates communication and partnership among scientists in fields as diverse as biology, chemistry, mathematics, medicine, and environmental science. This interdisciplinary discourse is essential not only for the success of independent and collaborative research and teaching programs, but also for the continued interest in the use of neural network tools in scientific inquiry. The book covers: A brief history of computational neural network models in relation to brain function Neural network operations, including neuron connectivity and layer arrangement Basic building blocks of model design, selection, and application from a statistical perspective Neurofuzzy systems, neuro-genetic systems, and neuro-fuzzy-genetic systems Function of neural networks in the study of complex natural processes Scientists deal with very complicated systems, much of the inner workings of which are frequently unknown to researchers. Using only simple, linear mathematical methods, information that is needed to truly understand natural systems may be lost. The development of new algorithms to model such processes is needed, and ANNs can play a major role. Balancing basic principles and diverse applications, this text introduces newcomers to the field and reviews recent developments of interest to active neural network practitioners.

Artificial Neural Networks and Machine Learning ICANN 2019 Workshop and Special Sessions

Artificial Neural Networks and Machine Learning     ICANN 2019  Workshop and Special Sessions Book
Author : Igor V. Tetko,Věra Kůrková,Pavel Karpov,Fabian Theis
Publisher : Springer Nature
Release : 2019-09-10
ISBN : 3030304930
Language : En, Es, Fr & De

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Book Description :

The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions.

Data Processing Techniques and Applications for Cyber Physical Systems DPTA 2019

Data Processing Techniques and Applications for Cyber Physical Systems  DPTA 2019  Book
Author : Chuanchao Huang,Yu-Wei Chan,Neil Yen
Publisher : Springer Nature
Release : 2020-02-03
ISBN : 9811514682
Language : En, Es, Fr & De

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Book Description :

This book covers cutting-edge and advanced research on data processing techniques and applications for Cyber-Physical Systems. Gathering the proceedings of the International Conference on Data Processing Techniques and Applications for Cyber-Physical Systems (DPTA 2019), held in Shanghai, China on November 15–16, 2019, it examines a wide range of topics, including: distributed processing for sensor data in CPS networks; approximate reasoning and pattern recognition for CPS networks; data platforms for efficient integration with CPS networks; and data security and privacy in CPS networks. Outlining promising future research directions, the book offers a valuable resource for students, researchers and professionals alike, while also providing a useful reference guide for newcomers to the field.

Encyclopedia of Molecular Biology

Encyclopedia of Molecular Biology Book
Author : Thomas E. Creighton
Publisher : Wiley-Interscience
Release : 1999
ISBN :
Language : En, Es, Fr & De

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Book Description :

The field of molecular biology has revolutionized the study of biology. The applications to medicine are enormous, ranging from diagnostic techniques for disease and genetic disorders, to drugs, to gene therapy. Focusing on the fundamentals of molecular biology and encompassing all aspects of the expression of genetic information, the Encyclopedia of Molecular Biology will become the first point of reference for both newcomers and established professionals in molecular biology needing to learn about any particular aspect of the field.

Applications of Metaheuristics in Process Engineering

Applications of Metaheuristics in Process Engineering Book
Author : Jayaraman Valadi,Patrick Siarry
Publisher : Springer
Release : 2014-08-07
ISBN : 3319065084
Language : En, Es, Fr & De

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Book Description :

Metaheuristics exhibit desirable properties like simplicity, easy parallelizability and ready applicability to different types of optimization problems such as real parameter optimization, combinatorial optimization and mixed integer optimization. They are thus beginning to play a key role in different industrially important process engineering applications, among them the synthesis of heat and mass exchange equipment, synthesis of distillation columns and static and dynamic optimization of chemical and bioreactors. This book explains cutting-edge research techniques in related computational intelligence domains and their applications in real-world process engineering. It will be of interest to industrial practitioners and research academics.

Proceedings

Proceedings Book
Author : American Association for Artificial Intelligence
Publisher :
Release : 1990
ISBN :
Language : En, Es, Fr & De

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Book Description :

AI and Education. Automated Reasoning: automatic programming, planning and scheduling, rule-based reasoning, search, theorem proving, uncertainty, truth-maintenance systems, constraint-based systems. Cognitive Modeling. Commonsense Reasoning: qualitative reasoning, design, diagnosis, simulation. Impacts of AI Technology: organizational, economic, and social implications. Knowledge Acquisition and Expert System Design Methodologies: techniques for designing expert systems and acquiring domain knowledge. Knowledge Representation: knowledge-representation systems, inheritance, nonmonotonic logic, nonstandard logics, temporal reasoning. Machine Architectures and Computer Languages for AI. Machine Learning. Natural Language: generation and understanding; syntax, speech, dialogue. Perception and Signal Understanding: vision. Philosophical Foundations. Robotics. User Interfaces.

Handbook of Neural Computation

Handbook of Neural Computation Book
Author : Pijush Samui,Sanjiban Sekhar Roy,Valentina E. Balas
Publisher : Academic Press
Release : 2017-07-18
ISBN : 0128113197
Language : En, Es, Fr & De

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Book Description :

Handbook of Neural Computation explores neural computation applications, ranging from conventional fields of mechanical and civil engineering, to electronics, electrical engineering and computer science. This book covers the numerous applications of artificial and deep neural networks and their uses in learning machines, including image and speech recognition, natural language processing and risk analysis. Edited by renowned authorities in this field, this work is comprised of articles from reputable industry and academic scholars and experts from around the world. Each contributor presents a specific research issue with its recent and future trends. As the demand rises in the engineering and medical industries for neural networks and other machine learning methods to solve different types of operations, such as data prediction, classification of images, analysis of big data, and intelligent decision-making, this book provides readers with the latest, cutting-edge research in one comprehensive text. Features high-quality research articles on multivariate adaptive regression splines, the minimax probability machine, and more Discusses machine learning techniques, including classification, clustering, regression, web mining, information retrieval and natural language processing Covers supervised, unsupervised, reinforced, ensemble, and nature-inspired learning methods

Artificial Intelligence in Chemical Engineering

Artificial Intelligence in Chemical Engineering Book
Author : Thomas E. Quantrille,Yih An Liu
Publisher :
Release : 1991
ISBN :
Language : En, Es, Fr & De

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Book Description :

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. Key Features * 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