Handbook of Probabilistic Models

Handbook of Probabilistic Models carefully examines the application of advanced probabilistic models in conventional engineering fields. In this comprehensive handbook, practitioners, researchers and scientists will find detailed explanations of technical concepts, applications of the proposed methods, and the respective scientific approaches needed to solve the problem. This book provides an interdisciplinary approach that creates advanced probabilistic models for engineering fields, ranging from conventional fields of mechanical engineering and civil engineering, to electronics, electrical, earth sciences, climate, agriculture, water resource, mathematical sciences and computer sciences.
Specific topics covered include minimax probability machine regression, stochastic finite element method, relevance vector machine, logistic regression, Monte Carlo simulations, random matrix, Gaussian process regression, Kalman filter, stochastic optimization, maximum likelihood, Bayesian inference, Bayesian update, kriging, copula-statistical models, and more.

List of contents

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

Product details

• Assisted by: Subrata Chakraborty (Editor), Chakraborty Subrata (Editor), Ravinesh Deo (Editor), Pijush Samui (Editor), Samui Pijush (Editor), Dieu Tien Bui (Editor)
• Publisher: Elsevier Science & Technology
• Languages: English
• Product format: Paperback / Softback
• Released: 08.10.2019
• EAN: 9780128165140
• ISBN: 978-0-12-816514-0
• Dimensions: 152 mm x 27 mm x 229 mm
• Weight: 880 g
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Miscellaneous; TECHNOLOGY & ENGINEERING / General, MATHEMATICS / Applied, TECHNOLOGY & ENGINEERING / Civil / General, COMPUTERS / Information Technology, COMPUTERS / Computer Simulation, information architecture, Applied mathematics, Maths for engineers, Civil engineering, surveying & building, Computer modelling & simulation, Database design and theory, COMPUTERS / Data Science / Data Modeling & Design, Civil engineering, surveying and building, Database design & theory