Combining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications
How can we solve engineering problems while taking into account data characterized by different types of measurement and estimation uncertainty: interval, probabilistic, fuzzy, etc.? This book provides a theoretical basis for arriving at such solutions, as well as case studies demonstrating how thes...
| Main Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
Cham
Springer International Publishing
2018, 2018
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| Edition: | 1st ed. 2018 |
| Series: | Studies in Computational Intelligence
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| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Introduction
- How to Get More Accurate Estimates
- How to Speed Up Computations
- Towards a Better Understandability of Uncertainty-Estimating Algorithms
- How General Can We Go: What Is Computable and What Is Not
- Decision Making Under Uncertainty
- Conclusions