Logo - springer
Slogan - springer

Statistics - Physical & Information Science | Uncertainty Forecasting in Engineering

Uncertainty Forecasting in Engineering

Möller, Bernd, Reuter, Uwe

2007, XIV, 202 p.

Available Formats:

Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.

You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.

After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.


(net) price for USA

ISBN 978-3-540-37176-2

digitally watermarked, no DRM

Included Format: PDF

download immediately after purchase

learn more about Springer eBooks

add to marked items


Hardcover version

You can pay for Springer Books with Visa, Mastercard, American Express or Paypal.

Standard shipping is free of charge for individual customers.


(net) price for USA

ISBN 978-3-540-37173-1

free shipping for individuals worldwide

online orders shipping within 2-3 days.

add to marked items


Softcover (also known as softback) version.

You can pay for Springer Books with Visa, Mastercard, American Express or Paypal.

Standard shipping is free of charge for individual customers.


(net) price for USA

ISBN 978-3-642-07205-5

free shipping for individuals worldwide

usually dispatched within 3 to 5 business days

add to marked items

  • Fuzzy time series can be applied in many fields in engineering, such as environmental engineering or civil engineering
  • Explains two important, simulation-based forecasting strategies: fuzzy-white-noise-processes and fuzzy artificial neural networks
  • Offers a complete new description of uncertain data as incremental fuzzy data

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.

Content Level » Research

Keywords » Forecasting - Fuzzy Data - Fuzzy artificial neutral networks - Measure - Random Values - Time series - Uncertainty - artificial neural network - fuzzy

Related subjects » Civil Engineering - Mechanics - Monitoring & Environmental Analysis - Physical & Information Science - Probability Theory and Stochastic Processes

Table of contents / Sample pages 

Popular Content within this publication 



Read this Book on Springerlink

Services for this book

New Book Alert

Get alerted on new Springer publications in the subject area of Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.