Handbook of Probabilistic Models
1st Edition
Description
Used to define the risk in any engineering project, the development and the appropriate application of probabilistic models is a critical part of the design and analysis process in any engineering operation. A definitive reference for understanding and creating more effective models, Handbook of Probabilistic Models carefully examines the applications of advanced probabilistic models in conventional engineering fields. In this Handbook, practitioners, researchers, and scientist will find detailed explanations of the technical concept, applications of the proposed methods and the respective scientific approaches to solve the problem.
Handbook of Probabilistic Models provides an interdisciplinary approach to create advanced probabilistic models for engineering fields ranging from conventional fields of mechanical engineering, civil engineering to electronics, electrical, earth sciences, climate, agriculture, water resource, mathematical sciences and computer sciences. The authors cover topics such as: 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, etc.
Key Features
- Explains the application of advanced probabilistic models encompassing multi-disciplinary research
- Application of probabilistic modelling to various emerging areas in Engineering
- Provides and interdisciplinary approach to probabilistic models and their applications to solve a wide range of practical problems
Readership
Civil Engineers, Environmental Engineers, Chemical Engineers, Mechanical Engineers, Agricultural Engineers, Environmental Scientists and Industrial Engineers
Table of Contents
- 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
Details
- No. of pages:
- 612
- Language:
- English
- Copyright:
- © Butterworth-Heinemann 2020
- Published:
- 1st September 2019
- Imprint:
- Butterworth-Heinemann
- Paperback ISBN:
- 9780128165140
About the Author
Pijush Samui
Pijush Samui is working as an associate professor in civil engineering department at NIT Patna, India. He graduated in 2000, with a B.Tech. in Civil Engineering from Indian Institute of Engineering Science and Technology, Shibpur, India. He received his M.Sc. in Geotechnical Earthquake Engineering from Indian Institute of Science, Bangalore, India (2004). He holds a Ph.D. in Geotechnical Earthquake Engineering (2008) from Indian Institute of Science, Bangalore, India. He was a postdoctoral fellow at University of Pittsburgh (USA) (2008-2009) and Tampere University of Technology (Finland) (2009- 2010). In 2010, Dr. Pijush joined in the Center for Disaster Mitigation and Management at VIT University as an Associate Professor. He was promoted to full Professor in 2012. Dr. Pijush is the recipient of the prestigious CIMO fellowship (2009) from Finland, for his integrated research on the design of railway embankment. He was awarded Shamsher Prakash Research Award (2011) by IIT Roorkee for his innovative research on the application of Artificial Intelligence in designing civil engineering structure. He was selected as the recipient of IGS Sardar Resham Singh Memorial Award – 2013 for his innovative research on infrastructure project. He was elected Fellow of International Congress of Disaster Management in 2010. He served as a guest in disaster advance journal. He also serves as an editorial board member in several international journals. He has been selected as an adjunct professor at Ton Duc Thang University (Ho Chi Minh City, Vietnam). He has been Visiting Professor at Far East Federal University (Russia).
Affiliations and Expertise
Associate Professor, Department of Civil Engineering, NIT Patna, Bihar, India
Dieu Tien Bui
Dieu Tien Bui is in the Geographic Information System Group, Department of Business and IT at the University of South-Eastern Norway, Norway.
Affiliations and Expertise
Geographic Information System Group, Department of Business and IT, University of South-Eastern Norway, Norway
Subrata Chakraborty
Dr. Subrata Chakraborty is currently a Professor and former Head of Civil Engineering Department at the Indian Institute of Engineering Science and Technology, Shibpur. He is a fellow of the Indian National Academy Engineering. Prof. Chakraborty did his Bachelor in Civil Engineering from Bengal Engineering College, Shibpur, M. Tech. and PhD from IIT Kharagpur. He was a postdoctoral researcher at University of Cambridge, UK and University of Arizona, USA and Technical University of Aachen, Germany. In general, Prof. Chakraborty’s research interests are in the field of computational mechanics under uncertainty, structural health monitoring, vibration control, composite mechanics etc. He has published extensively in peer reviewed journals, authored textbook and book chapters and reviewed research articles for various national and international journals. As an independent researcher, he has completed a number of research projects funded by various agencies and is also active in important industrial consultancy. While his inspiring teaching coupled with innate urge for intensive research has already established him as a distinguished academician at the national level, several awards and laurels have come his way. The Humboldt Fellowship for Experienced Researchers, the V. H. Joshi Award for Significant Contributions in Structural Dynamics, the INAE Young Engineer Award, the BOYSCAST Fellowship, and the Young Faculty Research Award deserve special mention.
Affiliations and Expertise
FNAE, Professor and Former Head, Department of Civil Engineering, Indian Institute of Engineering Science and Technology
Ravinesh Deo
Dr Ravinesh Deo obtained BSc (with Gold Medal) from University of the South Pacific, MSc (Honours) from University of Canterbury and PhD from Adelaide University including Graduate Certificate in Tertiary Teaching from University of Southern Queensland. At The University of Queensland Dr Deo worked as Postdoctoral Fellow followed by Principal Scientist with Queensland Government. Currently, he is Senior Lecturer with significant doctoral supervision and project leadership at University of Southern Queensland. Dr Deo held Senior Visiting Researcher positons at United States Smithsonian Tropical Research Institute, McGill University, Chinese Academy of Science, University of Tokyo, including Kyoto and Kyushu University, Peking University, National University of Singapore and Universidad de Alcalá. Dr Deo is Associate Editor of ASCE Journal of Hydrologic Engineering, Editorial Board Member of Hydrology Research and Editor for Energies (SI). He won internationally prestigious fellowships and grants such as the Queensland Smithsonian Fellowship, Australia-China Young Scientist Award, Japan Society for Promotion of Science (JSPS) Fellowship, Chinese Academy of Science Fellowship and Australian Endeavour Fellowship. He teaches engineering mathematics, and leads artificial intelligence research whilst successfully supervised many doctoral and masters’ students. Dr Deo has published more than 150 peer reviewed papers that includes more than 100 Journal articles (high ranked), 2 Edited Books, Book Chapters and Conference papers in artificial intelligence, decision systems, energy, health informatics, and water and climate science.
Affiliations and Expertise
School of Agricultural Computational and Environmental Sciences, Institute of Life Science and the Environment, University of Southern Queensland, Springfield, Australia