Overview
- Provides a generic methodology with elaborated algorithmic image of probabilistic, possibly adaptive, optimised advisory system supporting dynamic decision making under uncertainty in a complex environment
- Dynamic, adaptive, mixture modelling of non-linear uncertain systems from le6 data records, each having several tens of entries, has not been done before
- Optimization of advises in a fully probabilistic sense has not been done before
- Brings a completely new treatment of the topic of supervisory control of nonlinear uncertain systems to the fore
- Neither book nor solution, have a viable competitor
- Original problem formulation and practical solution of the optimised and adaptive advising
- Many particular, often novel, results widely applicable in signal processing, modelling and estimation of non-linear systems, multi-step prediction, pattern recognition and (adaptive) control
- Diverse application potential from technological processes, medical diagnostics, control of urban traffic to economical and societal processes
- Includes supplementary material: sn.pub/extras
Part of the book series: Advanced Information and Knowledge Processing (AI&KP)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
About this book
Similar content being viewed by others
Keywords
Table of contents (15 chapters)
Editors and Affiliations
Bibliographic Information
Book Title: Optimized Bayesian Dynamic Advising
Book Subtitle: Theory and Algorithms
Editors: Miroslav Karny
Series Title: Advanced Information and Knowledge Processing
DOI: https://doi.org/10.1007/1-84628-254-3
Publisher: Springer London
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag London 2006
Hardcover ISBN: 978-1-85233-928-9Published: 10 October 2005
Softcover ISBN: 978-1-4471-5675-8Published: 20 October 2014
eBook ISBN: 978-1-84628-254-6Published: 19 December 2005
Series ISSN: 1610-3947
Series E-ISSN: 2197-8441
Edition Number: 1
Number of Pages: XVII, 529
Topics: Models and Principles, User Interfaces and Human Computer Interaction, Artificial Intelligence, Simulation and Modeling, Pattern Recognition, Statistics and Computing/Statistics Programs