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Clustering, Classification, and Time Series Prediction by Using Artificial Neural Networks (Record no. 63801)

MARC details
000 -LEADER
fixed length control field 04018nam a22005295i 4500
001 - CONTROL NUMBER
control field 978-3-031-71101-5
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251030113112.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 240928s2024 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783031711015
-- 978-3-031-71101-5
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-031-71101-5
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q342
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQ
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM004000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQ
Source thema
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Melin, Patricia.
Relator term author.
Authority record control number (orcid)0000-0001-5798-1426
-- https://orcid.org/0000-0001-5798-1426
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
9 (RLIN) 74912
245 10 - TITLE STATEMENT
Title Clustering, Classification, and Time Series Prediction by Using Artificial Neural Networks
Medium [electronic resource] /
Statement of responsibility, etc. by Patricia Melin, Martha Ramirez, Oscar Castillo.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2024.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Cham :
Name of producer, publisher, distributor, manufacturer Springer Nature Switzerland :
-- Imprint: Springer,
Date of production, publication, distribution, manufacture, or copyright notice 2024.
300 ## - PHYSICAL DESCRIPTION
Extent VIII, 74 p. 21 illus., 20 illus. in color.
Other physical details online resource.
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
347 ## - DIGITAL FILE CHARACTERISTICS
File type text file
Encoding format PDF
Source rda
490 1# - SERIES STATEMENT
Series statement SpringerBriefs in Computational Intelligence,
International Standard Serial Number 2625-3712
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 1. Introduction to Prediction with Neural Networks -- 2. Literature Review on Prediction with Neural Networks -- 3. Problem Description of Prediction with Neural Networks -- 4. Methodology for Prediction with Neural Networks5 -- Results of Prediction with Neural Networks -- 6. Discussion of Prediction Results with Neural Networks -- 7. Conclusions for Prediction with Neural Networks.
520 ## - SUMMARY, ETC.
Summary, etc. This book provides a new model for clustering, classification, and time series prediction by using artificial neural networks to computationally simulate the behavior of the cognitive functions of the brain is presented. This model focuses on the study of intelligent hybrid neural systems and their use in time series analysis and decision support systems. Therefore, through the development of eight case studies, multiple time series related to the following problems are analyzed: traffic accidents, air quality and multiple global indicators (energy consumption, birth rate, mortality rate, population growth, inflation, unemployment, sustainable development, and quality of life). The main contribution consists of a Generalized Type-2 fuzzy integration of multiple indicators (time series) using both supervised and unsupervised neural networks and a set of Type-1, Interval Type-2, and Generalized Type-2 fuzzy systems. The obtained results show the advantages of the proposed model of Generalized Type-2 fuzzy integration of multiple time series attributes. This book is intended to be a reference for scientists and engineers interested in applying type-2 fuzzy logic techniques for solving problems in classification and prediction. We consider that this book can also be used to get novel ideas for new lines of research, or to continue the lines of research proposed by the authors of the book.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element
9 (RLIN) 64052
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element
9 (RLIN) 64145
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element
9 (RLIN) 64052
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element
9 (RLIN) 64145
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Ramirez, Martha.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
9 (RLIN) 85196
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Castillo, Oscar.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
9 (RLIN) 66767
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9783031711008
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9783031711022
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title SpringerBriefs in Computational Intelligence,
International Standard Serial Number 2625-3712
9 (RLIN) 74073
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-3-031-71101-5">https://doi.org/10.1007/978-3-031-71101-5</a>
912 ## -
-- ZDB-2-INR
912 ## -
-- ZDB-2-SXIT

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