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Uncertainty Forecasting in Engineering

:	Bernd Möller, Uwe Reuter
:	Uncertainty Forecasting in Engineering
:	Springer-Verlag
:	9783540371762
:	1
:	CHF 87.50
:

:	Naturwissenschaften allgemein
:	English

:	202
:	Wasserzeichen/DRM
:	PC/MAC/eReader/Tablet
:	PDF

Observat ons of uncertainty in measured data with time improves forecasting capability in a wide range of fields in engineering. This book provides an introduction to uncertainty forecasting based on fuzzy time series. It details descriptive, modeling, and forecasting methods for fuzzy time series. Coverage places emphasis on forecasting based on fuzzy random processes as well as forecasting involving fuzzy neuronal networks.

^{Univ.-Prof. Dr.-Ing. habil. Bernd Möller (*1941) studied civil engineering. From 1994 -1996 he was professor for Numerical Methods and Computer Science in Engineering at the University of Braunschweig, and from 1996 - 2006 professor for Solid and Structural Mechanics at the University of Technology in Dresden, Germany. Professor Möller has been retired since 2006.
Dr.-Ing. Uwe Reuter (*1979) studied civil engineering. From 2003 - 2007 he was research associate at the Institute of Statics and Dynamics of Structures at the University of Technology in Dresden, Germany. Today he is head of the Computing Center at the Faculty of Civil Engineering at the University of Technology in Dresden.}

	Preface	5
	Contents	7
	Abbreviations	9
	1 Introduction	14
	1.1 Application of Time Series for Forecasting in Engineering	14
	1.2 Data Uncertainty and Fuzzy Time Series	18
	1.3 Examples of Fuzzy Time Series	20
	2 Mathematical Description of Uncertain Data	22
	2.1 Fuzzy Variables	22
	2.2 Fuzzy Random Variables	38
	2.3 Fuzzy Random Processes	66
	3 Analysis of Time Series Comprised of Uncertain Data	71
	3.1 Plot of Fuzzy Time Series	71
	3.2 Fuzzy Component Model	75
	3.3 Stationary Fuzzy Time Series	81
	3.4 Transformation of Fuzzy Time Series Using Filters	86
	3.5 Modeling on the Basis of Specific Fuzzy Random Processes	91
	3.6 Modeling on the Basis of Artificial Neural Networks	118
	4 Forecasting of Time Series Comprised of Uncertain Data	142
	4.1 Underlying Concept	142
	4.2 Forecasting on the Basis of Specific Fuzzy Random Processes	145
	4.3 Forecasting on the Basis of Artificial Neural Networks	155
	5 Uncertain Forecasting in Engineering and Environmental Science	164
	5.1 Model-Free Forecasting	164
	5.2 Model-Based Forecasting	166
	5.3 Applications	174
	References	203
	Index	208