Uncertainty Forecasting in Engineering
Autor Bernd Möller, Uwe Reuteren Limba Engleză Hardback – 21 aug 2007
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Specificații
ISBN-13: 9783540371731
ISBN-10: 3540371737
Pagini: 212
Ilustrații: XIV, 202 p.
Dimensiuni: 155 x 235 x 19 mm
Greutate: 0.43 kg
Ediția:2007
Editura: Springer Berlin, Heidelberg
Colecția Springer
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3540371737
Pagini: 212
Ilustrații: XIV, 202 p.
Dimensiuni: 155 x 235 x 19 mm
Greutate: 0.43 kg
Ediția:2007
Editura: Springer Berlin, Heidelberg
Colecția Springer
Locul publicării:Berlin, Heidelberg, Germany
Public țintă
ResearchCuprins
Mathematical Description of Uncertain Data.- Analysis of Time Series Comprised of Uncertain Data.- Forecasting of Time Series Comprised of Uncertain Data.- Uncertain Forecasting in Engineering and Environmental Science.
Recenzii
From the reviews:
"The authors deal with a new and fascinating subject: forcasting the incertainty in civil engineering and environmental science. … the volume is a scientific monograph and represents a valuable contribution to the field. It is intended for civil engineers as well as to many professionals working in related fields." (Petre P. Teodorescu, Zentralblatt MATH, Vol. 1131 (9), 2008)
"The authors deal with a new and fascinating subject: forcasting the incertainty in civil engineering and environmental science. … the volume is a scientific monograph and represents a valuable contribution to the field. It is intended for civil engineers as well as to many professionals working in related fields." (Petre P. Teodorescu, Zentralblatt MATH, Vol. 1131 (9), 2008)
Notă biografică
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.
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.
Textul de pe ultima copertă
This book deals with uncertainty forecasting based on a fuzzy time series approach, including fuzzy random processes and artificial neural networks. A consideration of data and measurement uncertainty enhances forecasting in a wide range of applications, particularly in the fields of engineering, environmental science and civil engineering.
Uncertain data are described by means of a new incremental fuzzy representation which permits a complete and accurate estimation of uncertainty.
The book is aimed at engineers as well as professionals working in related fields. Descriptive, modeling and forecasting methods pertaining to fuzzy time series are introduced and explained in detail. Emphasis is placed on forecasting with the aid of fuzzy random processes, such as fuzzy ARMA processes and fuzzy white-noise processes, as well as forecasting based on artificial neural networks.
All numerical algorithms are comprehensively described and demonstrated by way of practical examples.
Uncertain data are described by means of a new incremental fuzzy representation which permits a complete and accurate estimation of uncertainty.
The book is aimed at engineers as well as professionals working in related fields. Descriptive, modeling and forecasting methods pertaining to fuzzy time series are introduced and explained in detail. Emphasis is placed on forecasting with the aid of fuzzy random processes, such as fuzzy ARMA processes and fuzzy white-noise processes, as well as forecasting based on artificial neural networks.
All numerical algorithms are comprehensively described and demonstrated by way of practical examples.
Caracteristici
Fuzzy time series can be applied in many fields in engineering like environmental engineering or civil engineering Two simulation-based important forecasting strategies are explained: forecasting based on fuzzy-ARMA-processes or fuzzy-white-noise-processes and forecasting based on fuzzy artificial neural networks A complete new description of uncertain data as incremental fuzzy data is given Includes supplementary material: sn.pub/extras