Optimization, Uncertainty and Machine Learning in Wind Energy Conversion Systems
| Corporate Author: | |
|---|---|
| Other Authors: | , , |
| Summary: | XXI, 266 p. 120 illus., 104 illus. in color. text |
| Language: | English |
| Published: |
Singapore :
Springer Nature Singapore : Imprint: Springer,
2025.
|
| Edition: | 1st ed. 2025. |
| Series: | Engineering Optimization: Methods and Applications,
|
| Subjects: | |
| Online Access: | https://doi.org/10.1007/978-981-97-7909-3 |
| Format: | Electronic Book |
Table of Contents:
- Part 1 State-of-the-art in Optimization, Uncertainty handling, Machine Learning methods, and Wake models
- Chapter 1. Introduction
- Chpater 2. Multi-objective optimisation with uncertainty: considerations for wind farm optimisation
- Chapter 3. Offline Multi-Objective Optimisation using Surrogate-Assisted Evolutionary Algorithms with Uncertainty Quantification
- Chapter 4. Bayesian optimisation for expensive computational fluid dynamics design problems
- Chapter 5. Multidisciplinary uncertainty modelling using Copulas.