Uncertainty Forecasting in Engineering

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, en...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Möller, Bernd (Συγγραφέας), Reuter, Uwe (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2007.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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100 1 |a Möller, Bernd.  |e author. 
245 1 0 |a Uncertainty Forecasting in Engineering  |h [electronic resource] /  |c by Bernd Möller, Uwe Reuter. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg,  |c 2007. 
300 |a XIV, 202 p.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
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505 0 |a 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. 
520 |a 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. 
650 0 |a Statistics. 
650 0 |a Probabilities. 
650 0 |a Mechanics. 
650 0 |a Mechanics, Applied. 
650 0 |a Buildings  |x Design and construction. 
650 0 |a Building. 
650 0 |a Construction. 
650 0 |a Engineering, Architectural. 
650 1 4 |a Statistics. 
650 2 4 |a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. 
650 2 4 |a Theoretical and Applied Mechanics. 
650 2 4 |a Environmental Monitoring/Analysis. 
650 2 4 |a Building Construction. 
650 2 4 |a Probability Theory and Stochastic Processes. 
700 1 |a Reuter, Uwe.  |e author. 
710 2 |a SpringerLink (Online service) 
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776 0 8 |i Printed edition:  |z 9783540371731 
856 4 0 |u http://dx.doi.org/10.1007/978-3-540-37176-2  |z Full Text via HEAL-Link 
912 |a ZDB-2-SMA 
950 |a Mathematics and Statistics (Springer-11649)