Artificial Organic Networks (Record no. 57792)

000 -LEADER
fixed length control field 04088nam a22005415i 4500
001 - CONTROL NUMBER
control field 978-3-319-02472-1
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200421112228.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 131112s2014 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783319024721
-- 978-3-319-02472-1
082 04 - CLASSIFICATION NUMBER
Call Number 006.3
100 1# - AUTHOR NAME
Author Ponce-Espinosa, Hiram.
245 10 - TITLE STATEMENT
Title Artificial Organic Networks
Sub Title Artificial Intelligence Based on Carbon Networks /
300 ## - PHYSICAL DESCRIPTION
Number of Pages XII, 228 p. 192 illus., 56 illus. in color.
490 1# - SERIES STATEMENT
Series statement Studies in Computational Intelligence,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Introduction to Modeling Problems -- Chemical Organic Compounds -- Artificial Organic Networks -- Artificial Hydrocarbon Networks -- Enhancements of Artificial Hydrocarbon Networks -- Notes on Modeling Problems Using Artificial Hydrocarbon Networks -- Applications of Artificial Hydrocarbon Networks.-Appendices.
520 ## - SUMMARY, ETC.
Summary, etc 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™ 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.
700 1# - AUTHOR 2
Author 2 Ponce-Cruz, Pedro.
700 1# - AUTHOR 2
Author 2 Molina, Arturo.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-319-02472-1
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2014.
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Biochemical engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer simulation.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational intelligence.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence (incl. Robotics).
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Biochemical Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Simulation and Modeling.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 1860-949X ;
912 ## -
-- ZDB-2-ENG

No items available.