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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...
| Asıl Yazarlar: | , |
|---|---|
| Müşterek Yazar: | |
| Materyal Türü: | e-Kitap |
| Dil: | İngilizce |
| Baskı/Yayın Bilgisi: |
Cham :
Springer International Publishing :
2018.
Imprint: Springer, |
| Edisyon: | 1st ed. 2018. |
| Seri Bilgileri: | Studies in Computational Intelligence,
773 |
| Konular: | |
| Online Erişim: | Full-text access |
İçindekiler:
- 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.