Enhanced Machine Learning and Data Mining Methods for Analysing Large Hybrid Electric Vehicle Fleets based on Load Spectrum Data (Registro nro. 241535)

MARC details
000 -LIDER
fixed length control field 03463nam a22005535i 4500
001 - CONTROL NUMBER
control field 978-3-658-20367-2
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20210201191254.0
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 171201s2018 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783658203672
-- 978-3-658-20367-2
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TL1-483
072 #7 - SUBJECT CATEGORY CODE
Subject category code TRC
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code TEC009090
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code TRC
Source thema
072 #7 - SUBJECT CATEGORY CODE
Subject category code TRCS
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 629.2
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Bergmeir, Philipp.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
245 10 - TITLE STATEMENT
Title Enhanced Machine Learning and Data Mining Methods for Analysing Large Hybrid Electric Vehicle Fleets based on Load Spectrum Data
Medium [electronic resource] /
Statement of responsibility, etc. by Philipp Bergmeir.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2018.
264 #1 -
-- Wiesbaden :
-- Springer Fachmedien Wiesbaden :
-- Imprint: Springer Vieweg,
-- 2018.
300 ## - PHYSICAL DESCRIPTION
Extent XXXII, 166 p. 34 illus., 11 illus. in color.
Other physical details online resource.
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-- txt
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-- computer
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-- rdamedia
338 ## -
-- online resource
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347 ## -
-- text file
-- PDF
-- rda
490 1# - SERIES STATEMENT
Series statement Wissenschaftliche Reihe Fahrzeugtechnik Universität Stuttgart,
International Standard Serial Number 2567-0042
500 ## - GENERAL NOTE
General note Acceso multiusuario
520 ## - SUMMARY, ETC.
Summary, etc. Philipp Bergmeir works on the development and enhancement of data mining and machine learning methods with the aim of analysing automatically huge amounts of load spectrum data that are recorded for large hybrid electric vehicle fleets. In particular, he presents new approaches for uncovering and describing stress and usage patterns that are related to failures of selected components of the hybrid power-train. Contents Classifying Component Failures of a Vehicle Fleet Visualising Different Kinds of Vehicle Stress and Usage Identifying Usage and Stress Patterns in a Vehicle Fleet Target Groups  Students and scientists in the field of automotive engineering and data science Engineers in the automotive industry About the Author Philipp Bergmeir did a PhD in the doctoral program "Promotionskolleg HYBRID" at the Institute for Internal Combustion Engines and Automotive Engineering, University of Stuttgart, in cooperation with the Esslingen University of Applied Sciences and a well-known vehicle manufacturer. Currently, he is working as a data scientist in the automotive industry.
541 ## - IMMEDIATE SOURCE OF ACQUISITION NOTE
Owner UABC ;
Method of acquisition Temporal ;
Date of acquisition 01/01/2021-12/31/2023.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Automotive engineering.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Data mining.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Pattern recognition.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Automotive Engineering.
-- https://scigraph.springernature.com/ontologies/product-market-codes/T17047
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Data Mining and Knowledge Discovery.
-- https://scigraph.springernature.com/ontologies/product-market-codes/I18030
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Pattern Recognition.
-- https://scigraph.springernature.com/ontologies/product-market-codes/I2203X
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 9783658203665
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9783658203689
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Wissenschaftliche Reihe Fahrzeugtechnik Universität Stuttgart,
-- 2567-0042
856 40 - ELECTRONIC LOCATION AND ACCESS
Public note Libro electrónico
Uniform Resource Identifier http://148.231.10.114:2048/login?url=https://doi.org/10.1007/978-3-658-20367-2
912 ## -
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-- ZDB-2-SXE
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Libro Electrónico
Existencias
Estado de retiro Colección Ubicación permanente Ubicación actual Fecha de ingreso Total Checkouts Date last seen Número de copia Tipo de material
  Colección de Libros Electrónicos Biblioteca Electrónica Biblioteca Electrónica 01/02/2021   01/02/2021 1 Libro Electrónico

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