Stanford AA222/CS361 Engineering Design Optimization I Probabilistic Surrogate Optimization

Автор: Stanford Online

Загружено: 2023-06-06

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Описание:

In this lecture for Stanford's AA 222 / CS 361 Engineering Design Optimization course, we dive into the intricacies of Probabilistic Surrogate Optimization. The content covers key methodologies, including the development and use of surrogate models for efficient optimization of complex engineering designs. These comprehensive models are presented as critical tools for the evaluation and improvement of design performances. The lecture also emphasizes the application of probabilistic methods for managing uncertainty and improving decision-making in the design process.

Lecture Outline

Surrogate Model Selection
Probabilistic Surrogate Models
Gaussian Distributions
Gaussian Processes
Prediction
Noisy Measurements
Fitting Gaussian Processes

Surrogate Optimization
Exploration
Prediction-based
Error-based
Lower Confidence Bound
Probability of Improvement
Expected Improvement

Notebook: https://github.com/josh0tt/SurrogateO...
View the course website: https://aa222.stanford.edu/

Stanford AA222/CS361 Engineering Design Optimization I Probabilistic Surrogate Optimization

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