Elements of Artificial Neural Networks with Selected Applications in Chemical Engineering, and Chemical and Biological Sciences PDF Download
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Author: Sanjeev S. Tambe
Publisher: Simulation & Advanced Controls Incorporated
ISBN: 9780965163903
Category : Biology
Languages : en
Pages : 450
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Book Description
Author: Sanjeev S. Tambe
Publisher: Simulation & Advanced Controls Incorporated
ISBN: 9780965163903
Category : Biology
Languages : en
Pages : 450
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Book Description
Author:
Publisher: Allied Publishers
ISBN: 9788177640632
Category : Petroleum
Languages : en
Pages : 284
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Book Description
Author: Muthukumarasamy Karthikeyan
Publisher: Springer
ISBN: 8132217802
Category : Science
Languages : en
Pages : 546
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Book Description
Chemoinformatics is equipped to impact our life in a big way mainly in the fields of chemical, medical and material sciences. This book is a product of several years of experience and passion for the subject written in a simple lucid style to attract the interest of the student community who wish to master chemoinformatics as a career. The topics chosen cover the entire spectrum of chemoinformatics activities (methods, data and tools). The algorithms, open source databases, tutorials supporting theory using standard datasets, guidelines, questions and do it yourself exercises will make it valuable to the academic research community. At the same time every chapter devotes a section on development of new software tools relevant for the growing pharmaceutical, fine chemicals and life sciences industry. The book is intended to assist beginners to hone their skills and also constitute an interesting reading for the experts.
Author: Nguyen Ngoc Thach
Publisher: Springer Nature
ISBN: 3031591100
Category :
Languages : en
Pages : 724
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Book Description
Author: Grady Hanrahan
Publisher: CRC Press
ISBN: 1439812594
Category : Mathematics
Languages : en
Pages : 206
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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
Author: Petia Koprinkova-Hristova
Publisher: Springer
ISBN: 3319099035
Category : Technology & Engineering
Languages : en
Pages : 487
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Book Description
The book reports on the latest theories on artificial neural networks, with a special emphasis on bio-neuroinformatics methods. It includes twenty-three papers selected from among the best contributions on bio-neuroinformatics-related issues, which were presented at the International Conference on Artificial Neural Networks, held in Sofia, Bulgaria, on September 10-13, 2013 (ICANN 2013). The book covers a broad range of topics concerning the theory and applications of artificial neural networks, including recurrent neural networks, super-Turing computation and reservoir computing, double-layer vector perceptrons, nonnegative matrix factorization, bio-inspired models of cell communities, Gestalt laws, embodied theory of language understanding, saccadic gaze shifts and memory formation, and new training algorithms for Deep Boltzmann Machines, as well as dynamic neural networks and kernel machines. It also reports on new approaches to reinforcement learning, optimal control of discrete time-delay systems, new algorithms for prototype selection, and group structure discovering. Moreover, the book discusses one-class support vector machines for pattern recognition, handwritten digit recognition, time series forecasting and classification, and anomaly identification in data analytics and automated data analysis. By presenting the state-of-the-art and discussing the current challenges in the fields of artificial neural networks, bioinformatics and neuroinformatics, the book is intended to promote the implementation of new methods and improvement of existing ones, and to support advanced students, researchers and professionals in their daily efforts to identify, understand and solve a number of open questions in these fields.
Author: Pradeep K. Singh
Publisher: Allied Publishers
ISBN: 9385926403
Category : Fuel
Languages : en
Pages : 1562
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Book Description
The papers in these two volumes were presented at the International Conference on “NexGen Technologies for Mining and Fuel Industries” [NxGnMiFu-2017] in New Delhi from February 15-17, 2017, organized by CSIR-Central Institute of Mining and Fuel Research, Dhanbad, India. The proceedings include the contributions from authors across the globe on the latest research on mining and fuel technologies. The major issues focused on are: Innovative Mining Technology, Rock Mechanics and Stability Analysis, Advances in Explosives and Blasting, Mine Safety and Risk Management, Computer Simulation and Mine Automation, Natural Resource Management for Sustainable Development, Environmental Impacts and Remediation, Paste Fill Technology and Waste Utilisation, Fly Ash Management, Clean Coal Initiatives, Mineral Processing and Coal Beneficiation, Quality Coal for Power Generation and Conventional and Non-conventional Fuels and Gases. This collection of contemporary articles contains unique knowledge, case studies, ideas and insights, a must-have for researchers and engineers working in the areas of mining technologies and fuel sciences.
Author: David J. Livingstone
Publisher: Humana Press
ISBN: 9781588297181
Category : Computers
Languages : en
Pages : 254
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Book Description
In this book, international experts report the history of the application of ANN to chemical and biological problems, provide a guide to network architectures, training and the extraction of rules from trained networks, and cover many cutting-edge examples of the application of ANN to chemistry and biology. Methods involving the mapping and interpretation of Infra Red spectra and modelling environmental toxicology are included. This book is an excellent guide to this exciting field.
Author: Kishan Mehrotra
Publisher: MIT Press
ISBN: 9780262133289
Category : Computers
Languages : en
Pages : 376
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Book Description
Elements of Artificial Neural Networks provides a clearly organized general introduction, focusing on a broad range of algorithms, for students and others who want to use neural networks rather than simply study them. The authors, who have been developing and team teaching the material in a one-semester course over the past six years, describe most of the basic neural network models (with several detailed solved examples) and discuss the rationale and advantages of the models, as well as their limitations. The approach is practical and open-minded and requires very little mathematical or technical background. Written from a computer science and statistics point of view, the text stresses links to contiguous fields and can easily serve as a first course for students in economics and management. The opening chapter sets the stage, presenting the basic concepts in a clear and objective way and tackling important -- yet rarely addressed -- questions related to the use of neural networks in practical situations. Subsequent chapters on supervised learning (single layer and multilayer networks), unsupervised learning, and associative models are structured around classes of problems to which networks can be applied. Applications are discussed along with the algorithms. A separate chapter takes up optimization methods. The most frequently used algorithms, such as backpropagation, are introduced early on, right after perceptrons, so that these can form the basis for initiating course projects. Algorithms published as late as 1995 are also included. All of the algorithms are presented using block-structured pseudo-code, and exercises are provided throughout. Software implementing many commonly used neural network algorithms is available at the book's website. Transparency masters, including abbreviated text and figures for the entire book, are available for instructors using the text.
Author: CHADLI Mohammed
Publisher: Lavoisier
ISBN: 2746288257
Category :
Languages : en
Pages : 194
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Book Description
Pour représenter au mieux le fonctionnement dynamique d'un processus, une approche globale basée sur de multiples modèles LTI (linéaires ou affines) autour de différents points de fonctionnement est utilisée. Cette approche multimodèle est une représentation polytopique convexe pouvant être obtenue, soit directement à partir d'un modèle mathématique non linéaire, soit par transformation mathématique, soit par linéarisation autour de différents points de fonctionnement. Basé essentiellement sur la deuxième méthode de Lyapunov et la formulation LMI, Multimodèles en automatique se concentre sur l'analyse de la stabilité et la synthèse de correcteurs/observateurs. Le cas des multimodèles incertains avec des entrées inconnues est étudié et les fonctions de Lyapunov quadratiques et non quadratiques sont également considérées. Afin de réduire le pessimisme de la méthode quadratique, l'étude de stabilité des multimodèles est réalisée en considérant des fonctions de Lyapunov non quadratiques.
