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Author: Hiram Ponce-Espinosa Publisher: Springer ISBN: 3319024728 Category : Technology & Engineering Languages : en Pages : 232
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
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 Eredín Ponce Espinosa Publisher: ISBN: Category : Computer algorithms Languages : es Pages : 181
Book Description
"In this work, a new supervised learning method called artificial organic networks is proposed for modeling problems, i.e. fitting, analyzing, inference and classification. In fact, this technique is inspired on chemical organic compounds due to their characteristics of stability, encapsulation, inheritance, organization, and robustness. Additionally, this work presents artificial hydrocarbon networks, a supervised learning algorithm inspired on chemical hydrocarbon compounds and proposed under artificial organic networks technique. Theoretical and experimental results showed that both artificial organic networks technique and artificial hydrocarbon networks algorithm can be used for fitting functions, modeling systems, and inference and classification purposes."--Abstract p. ii.
Author: Alma Y. Alanis Publisher: Academic Press ISBN: 0128182474 Category : Science Languages : en Pages : 176
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. Presents the current trends for the solution of complex engineering problems that cannot be solved through conventional methods Includes real-life scenarios where a wide range of artificial neural network architectures can be used to solve the problems encountered in engineering Contains all the theory required to use the proposed methodologies for different applications
Author: Wolfgang Banzhaf Publisher: MIT Press ISBN: 0262551527 Category : Science Languages : en Pages : 572
Book Description
An introduction to the fundamental concepts of the emerging field of Artificial Chemistries, covering both theory and practical applications. The field of Artificial Life (ALife) is now firmly established in the scientific world, but it has yet to achieve one of its original goals: an understanding of the emergence of life on Earth. The new field of Artificial Chemistries draws from chemistry, biology, computer science, mathematics, and other disciplines to work toward that goal. For if, as it has been argued, life emerged from primitive, prebiotic forms of self-organization, then studying models of chemical reaction systems could bring ALife closer to understanding the origins of life. In Artificial Chemistries (ACs), the emphasis is on creating new interactions rather than new materials. The results can be found both in the virtual world, in certain multiagent systems, and in the physical world, in new (artificial) reaction systems. This book offers an introduction to the fundamental concepts of ACs, covering both theory and practical applications. After a general overview of the field and its methodology, the book reviews important aspects of biology, including basic mechanisms of evolution; discusses examples of ACs drawn from the literature; considers fundamental questions of how order can emerge, emphasizing the concept of chemical organization (a closed and self-maintaining set of chemicals); and surveys a range of applications, which include computing, systems modeling in biology, and synthetic life. An appendix provides a Python toolkit for implementing ACs.
Author: Juan M. García-Chamizo Publisher: Springer ISBN: 331926401X Category : Computers Languages : en Pages : 515
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: Minakhi Rout Publisher: Springer Nature ISBN: 3030338207 Category : Computers Languages : en Pages : 303
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: Pedro Ponce Publisher: BoD – Books on Demand ISBN: 9535125346 Category : Computers Languages : en Pages : 182
Book Description
This book has a complete set of applications of artificial neural networks that allow the reader to gain experience about the new systems for implementing and developing artificial intelligence (AI) methods, which can run in several digital systems. On the other hand, the book shows the newest algorithms of artificial intelligence that provide a wide spectrum of research areas in which AI can be deployed. There are a lot of books that address AI applications. However, this book shows the newest applications reached according with the technological changes that are presented nowadays. Those changes drastically appear in digital systems or other parallel areas that allow to improve the performance of AI algorithms. Hence, sometimes, the AI algorithms have to be redesigned in order to run in microcontrollers or FPGAs. The topics covered generate a structured book, so it could be used as a textbook, but it is designed to be accessible to a wide audience interested in AI.
Author: Lourdes Martínez-Villaseñor Publisher: Springer Nature ISBN: 3030337499 Category : Computers Languages : en Pages : 755
Book Description
This volume constitutes the proceedings of the 18th Mexican Conference on Artificial Intelligence, MICAI 2019, held in Xalapa, Mexico, in October/November 2019. The 59 full papers presented in this volume were carefully reviewed and selected from 148 submissions. They cover topics such as: machine learning; optimization and planning; fuzzy systems, reasoning and intelligent applications; and vision and robotics.
Author: Obdulia Pichardo Lagunas Publisher: Springer ISBN: 3319271016 Category : Computers Languages : en Pages : 638
Book Description
The two volume set LNAI 9413 + 9414 constitutes the proceedings of the 14th Mexican International Conference on Artificial Intelligence, MICAI 2015, held in Cuernavaca,. Morelos, Mexico, in October 2015. The total of 98 papers presented in these proceedings was carefully reviewed and selected from 297 submissions. They were organized in topical sections named: natural language processing; logic and multi-agent systems; bioinspired algorithms; neural networks; evolutionary algorithms; fuzzy logic; machine learning and data mining; natural language processing applications; educational applications; biomedical applications; image processing and computer vision; search and optimization; forecasting; and intelligent applications.
Author: Hiram Ponce-Espinosa
Author: Hiram Ponce-Espinosa
Author: Daniel S. Levine
Author: Hiram Eredín Ponce Espinosa
Author: Alma Y. Alanis
Author: Wolfgang Banzhaf
Author: Juan M. García-Chamizo
Author: Minakhi Rout
Author: Pedro Ponce
Author: Lourdes Martínez-Villaseñor
Author: Obdulia Pichardo Lagunas