Produktdetaljer
Biografisk notat
Univ.-Prof. Dr.-Ing. habil. Bernd Moller (*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 Moller 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.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)
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.