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Author: Hiram Ponce-Espinosa
Publisher: Springer
ISBN: 3319024728
Category : Technology & Engineering
Languages : en
Pages : 232
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Book Description
This monograph describes the synthesis and use of biologically-inspired artificial hydrocarbon networks (AHNs) for approximation models associated with machine learning and a novel computational algorithm with which to exploit them. The reader is first introduced to various kinds of algorithms designed to deal with approximation problems and then, via some conventional ideas of organic chemistry, to the creation and characterization of artificial organic networks and AHNs in particular. The advantages of using organic networks are discussed with the rules to be followed to adapt the network to its objectives. Graph theory is used as the basis of the necessary formalism. Simulated and experimental examples of the use of fuzzy logic and genetic algorithms with organic neural networks are presented and a number of modeling problems suitable for treatment by AHNs are described: · approximation; · inference; · clustering; · control; · classification; and · audio-signal filtering. The text finishes with a consideration of directions in which AHNs could be implemented and developed in future. A complete LabVIEWTM toolkit, downloadable from the book’s page at springer.com enables readers to design and implement organic neural networks of their own. The novel approach to creating networks suitable for machine learning systems demonstrated in Artificial Organic Networks will be of interest to academic researchers and graduate students working in areas associated with computational intelligence, intelligent control, systems approximation and complex networks.
Author: Hiram Ponce-Espinosa
Publisher: Springer
ISBN: 3319024728
Category : Technology & Engineering
Languages : en
Pages : 232
Get Book Here
Book Description
This monograph describes the synthesis and use of biologically-inspired artificial hydrocarbon networks (AHNs) for approximation models associated with machine learning and a novel computational algorithm with which to exploit them. The reader is first introduced to various kinds of algorithms designed to deal with approximation problems and then, via some conventional ideas of organic chemistry, to the creation and characterization of artificial organic networks and AHNs in particular. The advantages of using organic networks are discussed with the rules to be followed to adapt the network to its objectives. Graph theory is used as the basis of the necessary formalism. Simulated and experimental examples of the use of fuzzy logic and genetic algorithms with organic neural networks are presented and a number of modeling problems suitable for treatment by AHNs are described: · approximation; · inference; · clustering; · control; · classification; and · audio-signal filtering. The text finishes with a consideration of directions in which AHNs could be implemented and developed in future. A complete LabVIEWTM toolkit, downloadable from the book’s page at springer.com enables readers to design and implement organic neural networks of their own. The novel approach to creating networks suitable for machine learning systems demonstrated in Artificial Organic Networks will be of interest to academic researchers and graduate students working in areas associated with computational intelligence, intelligent control, systems approximation and complex networks.
Author: Alma Y Alanis
Publisher: Academic Press
ISBN: 0128182474
Category : Science
Languages : en
Pages : 176
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Book Description
Artificial Neural Networks for Engineering Applications presents current trends for the solution of complex engineering problems that cannot be solved through conventional methods. The proposed methodologies can be applied to modeling, pattern recognition, classification, forecasting, estimation, and more. Readers will find different methodologies to solve various problems, including complex nonlinear systems, cellular computational networks, waste water treatment, attack detection on cyber-physical systems, control of UAVs, biomechanical and biomedical systems, time series forecasting, biofuels, and more. Besides the real-time implementations, the book contains all the theory required to use the proposed methodologies for different applications.
Author: Joao Luis Garcia Rosa
Publisher: BoD – Books on Demand
ISBN: 9535127047
Category : Computers
Languages : en
Pages : 416
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Book Description
The idea of simulating the brain was the goal of many pioneering works in Artificial Intelligence. The brain has been seen as a neural network, or a set of nodes, or neurons, connected by communication lines. Currently, there has been increasing interest in the use of neural network models. This book contains chapters on basic concepts of artificial neural networks, recent connectionist architectures and several successful applications in various fields of knowledge, from assisted speech therapy to remote sensing of hydrological parameters, from fabric defect classification to application in civil engineering. This is a current book on Artificial Neural Networks and Applications, bringing recent advances in the area to the reader interested in this always-evolving machine learning technique.
Author: Minakhi Rout
Publisher: Springer Nature
ISBN: 3030338207
Category : Computers
Languages : en
Pages : 303
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Book Description
This book discusses the current research and concepts in data science and how these can be addressed using different nature-inspired optimization techniques. Focusing on various data science problems, including classification, clustering, forecasting, and deep learning, it explores how researchers are using nature-inspired optimization techniques to find solutions to these problems in domains such as disease analysis and health care, object recognition, vehicular ad-hoc networking, high-dimensional data analysis, gene expression analysis, microgrids, and deep learning. As such it provides insights and inspiration for researchers to wanting to employ nature-inspired optimization techniques in their own endeavors.
Author: Adel El-Shahat
Publisher: BoD – Books on Demand
ISBN: 9535137808
Category : Computers
Languages : en
Pages : 298
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Book Description
In this book, highly qualified multidisciplinary scientists grasp their recent researches motivated by the importance of artificial neural networks. It addresses advanced applications and innovative case studies for the next-generation optical networks based on modulation recognition using artificial neural networks, hardware ANN for gait generation of multi-legged robots, production of high-resolution soil property ANN maps, ANN and dynamic factor models to combine forecasts, ANN parameter recognition of engineering constants in Civil Engineering, ANN electricity consumption and generation forecasting, ANN for advanced process control, ANN breast cancer detection, ANN applications in biofuels, ANN modeling for manufacturing process optimization, spectral interference correction using a large-size spectrometer and ANN-based deep learning, solar radiation ANN prediction using NARX model, and ANN data assimilation for an atmospheric general circulation model.
Author: Chris Ferrie
Publisher: Sourcebooks, Inc.
ISBN: 149267382X
Category : Juvenile Nonfiction
Languages : en
Pages : 26
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Book Description
Fans of Chris Ferrie's ABCs of Economics, ABCs of Space, and Organic Chemistry for Babies will love this introduction to neural networks for babies and toddlers! Help your future genius become the smartest baby in the room! It only takes a small spark to ignite a child's mind. Neural Networks for Babies by Chris Ferrie is a colorfully simple introduction to the study of how machines and computing systems are created in a way that was inspired by the biological neural networks in animal and human brains. With scientific and mathematical information from an expert, this installment of the Baby University board book series is the perfect book for enlightening the next generation of geniuses. After all, it's never too early to become a scientist! If you're looking for programming for babies, coding for babies, or more Baby University board books to surprise your little one, look no further! Neural Networks for Babies offers fun early learning for your little scientist!
Author: Marco Cecarelli
Publisher: Academic Press
ISBN: 0128156600
Category : Technology & Engineering
Languages : en
Pages : 176
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Book Description
Design and Operation of Locomotion Systems examines recent advances in locomotion systems with multidisciplinary viewpoints, including mechanical design, biomechanics, control and computer science. In particular, the book addresses the specifications and requirements needed to achieve the proper design of locomotion systems. The book provides insights on the gait analysis of humans by considering image capture systems. It also studies human locomotion from a rehabilitation viewpoint and outlines the design and operation of exoskeletons, both for rehabilitation and human performance enhancement tasks. Additionally, the book content ranges from fundamental theory and mathematical formulations, to practical implementations and experimental testing procedures. - Written and contributed by leading experts in robotics and locomotion systems - Addresses humanoid locomotion from both design and control viewpoints - Discusses the design and control of multi-legged locomotion systems
Author: Juan M. García-Chamizo
Publisher: Springer
ISBN: 331926401X
Category : Computers
Languages : en
Pages : 515
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Book Description
This book constitutes the refereed proceedings of the 9th International Conference on Ubiquitous Computing and Ambient Intelligence, UCAmI 2015, held in Puerto Varas, Chile, in December 2015. The 36 full papers presented together with 11 short papers were carefully reviewed and selected from 62 submissions. The papers are grouped in topical sections on adding intelligence for environment adaption; ambient intelligence for transport; human interaction and ambient intelligence; and ambient intelligence for urban areas.
Author: James Devillers
Publisher: Academic Press
ISBN: 0080537383
Category : Technology & Engineering
Languages : en
Pages : 309
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Book Description
Comprehensive and impeccably edited, Neural Networks in QSAR and Drug Design is the first book to present an all-inclusive coverage of the topic. The book provides a practice-oriented introduction to the different neural network paradigms, allowing the reader to easily understand and reproduce the results demonstrated. Numerous examples are detailed, demonstrating a variety of applications to QSAR and drug design.The contributors include some of the most distinguished names in the field, and the book provides an exhaustive bibliography, guiding readers to all the literature related to a particular type of application or neural network paradigm. The extensive index acts as a guide to the book, and makes retrieving information from chapters an easy task. A further research aid is a list of software with indications of availablility and price, as well as the editors scale rating the ease of use and interest/price ratio of each software package. The presentation of new, powerful tools for modeling molecular properties and the inclusion of many important neural network paradigms, coupled with extensive reference aids, makes Neural Networks in QSAR and Drug Design an essential reference source for those on the frontiers of this field. - Presents the first coverage of neural networks in QSAR and Drug Design - Allows easy understanding and reproduction of the results described within - Includes an exhaustive bibliography with more than 200 references - Provides a list of applicable software packages with availability and price
Author: Hiram Eredín Ponce Espinosa
Publisher: Springer
ISBN: 3319262300
Category : Technology & Engineering
Languages : en
Pages : 295
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Book Description
The book presents recent advances in nature-inspired computing, giving a special emphasis to control systems applications. It reviews different techniques used for simulating physical, chemical, biological or social phenomena at the purpose of designing robust, predictive and adaptive control strategies. The book is a collection of several contributions, covering either more general approaches in control systems, or methodologies for control tuning and adaptive controllers, as well as exciting applications of nature-inspired techniques in robotics. On one side, the book is expected to motivate readers with a background in conventional control systems to try out these powerful techniques inspired by nature. On the other side, the book provides advanced readers with a deeper understanding of the field and a broad spectrum of different methods and techniques. All in all, the book is an outstanding, practice-oriented reference guide to nature-inspired computing addressing graduate students, researchers and practitioners in the field of control engineering.
