Handbook of Probabilistic Models

Explains engineering applications for a host of advanced probabilistic models, including the stochastic finite element method and copula-statistical models

Pijush Samui (Edited by), Dieu Tien Bui (Edited by), Subrata Chakraborty (Edited by), Ravinesh Deo (Edited by)

9780128165140

Paperback, published 8 October 2019

590 pages
22.9 x 15.1 x 3.6 cm, 0.88 kg

Approx.568 pages

1. Monte Carlo Simulation
2. Stochastic Optimization Method
3. Reliability Analysis
4. Stochastic Finite Element Method
5. Kalman Filter
6. Random matrix
7. Markov Chain
8. Gaussian Process Regression
9. Logistic regression
10. Geostatistics
11. Kriging
12. Bayesian inference
13. Bayesian updating
14. Probabilistic Neural Network
15. SVM, Relevance vector machine

Subject Areas: Computer modelling & simulation [UYM], Civil engineering, surveying & building [TN], Maths for engineers [TBJ], Technology: general issues [TB]