Artificial Organic Networks / Studies in Computational Intelligence Bd.521 (PDF)
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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 LabVIEW(TM) 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.
Dr. Hiram Ponce-Espinosa is the author of the novel artificial intelligence technique called Artificial Organic Networks and author of the supervised learning algorithm so-called Artificial Hydrocarbon Networks.
He graduated from Tecnológico de Monterrey CCM, Mexico with a B.S. in Mechatronics Engineering (2008) and a Specialty in Control and Automation (2009). He also received both his Master's Degree in Engineering Science with specialization in Intelligent Control (2010) and his Ph.D. in Computer Sciences with specialization in Artificial Intelligence (2013) from the same Institute.
He has published several research articles for both international conferences and journals, two books in the field of artificial intelligence and robotics, and he has participated in a chapter book at "LabVIEW: A Developer's Guide to Real-World Integration" (2012). He is also co-author of six patents, including the recognized third-party software "Intelligent Control Toolkit for LabVIEW" (ICTL).
He is currently co-founder and CEO at Solarium Labs, the first Mexican research center 100% dedicated to develop intelligent systems for academy and industry. He is also professor and researcher at Tecnológico de Monterrey CCM, Mexico. His main interests are: artificial intelligence, engineering control systems, machine learning, and education.
- Autoren: Hiram Ponce-Espinosa , Pedro Ponce-Cruz , Arturo Molina
- 2013, 2014, 228 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 3319024728
- ISBN-13: 9783319024721
- Erscheinungsdatum: 12.11.2013
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- Dateiformat: PDF
- Grösse: 8.96 MB
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