Machine Learning for Cyber Physical Systems (Record no. 79116)

000 -LEADER
fixed length control field 04205nam a22005415i 4500
001 - CONTROL NUMBER
control field 978-3-662-48838-6
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220801220937.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 160219s2016 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783662488386
-- 978-3-662-48838-6
082 04 - CLASSIFICATION NUMBER
Call Number 006.3
245 10 - TITLE STATEMENT
Title Machine Learning for Cyber Physical Systems
Sub Title Selected papers from the International Conference ML4CPS 2015 /
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2016.
300 ## - PHYSICAL DESCRIPTION
Number of Pages VI, 121 p. 12 illus. in color.
490 1# - SERIES STATEMENT
Series statement Technologien für die intelligente Automation, Technologies for Intelligent Automation,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Development of a Cyber-Physical System based on selective dynamic Gaussian naive Bayes model for a self-predict laser surface heat treatment process control -- Evidence Grid Based Information Fusion for Semantic Classifiers in Dynamic Sensor Networks -- Forecasting Cellular Connectivity for Cyber- Physical Systems: A Machine Learning Approach -- Towards Optimized Machine Operations by Cloud Integrated Condition Estimation -- Prognostics Health  Management System based on Hybrid Model to Predict Failures of a Planetary Gear Transmission -- Evaluation of Model-Based Condition Monitoring Systems in Industrial Application Cases -- Towards a novel learning assistant for networked automation systems -- Effcient Image Processing System for an Industrial Machine Learning Task -- Efficient engineering in special purpose machinery through automated control code synthesis based on a functional categorisation -- Geo-Distributed Analytics for the Internet of Things -- Imple mentation and Comparison of Cluster-Based PSO Extensions in Hybrid Settings with Efficient Approximation -- Machine-specifc Approach for Automatic Classifcation of Cutting Process Efficiency -- Meta-analysis of Maintenance Knowledge Assets Towards Predictive Cost Controlling of Cyber Physical Production Systems -- Towards Autonomously Navigating and Cooperating Vehicles in Cyber-Physical Production Systems.
520 ## - SUMMARY, ETC.
Summary, etc The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Lemgo, October 1-2, 2015. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.
700 1# - AUTHOR 2
Author 2 Niggemann, Oliver.
700 1# - AUTHOR 2
Author 2 Beyerer, Jürgen.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-662-48838-6
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Berlin, Heidelberg :
-- Springer Berlin Heidelberg :
-- Imprint: Springer Vieweg,
-- 2016.
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-- text
-- txt
-- rdacontent
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-- computer
-- c
-- rdamedia
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-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data mining.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Knowledge management.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data Mining and Knowledge Discovery.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Knowledge Management.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 2522-8587
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-- ZDB-2-ENG
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-- ZDB-2-SXE

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