Open access peer-reviewed Edited Volume

Dynamic Programming and Bayesian Inference

Concepts and Applications

Dynamic programming and Bayesian inference have been both intensively and extensively developed during recent years. Because of these developments, interest in dynamic programming and Bayesian inference and their applications has greatly increased at all mathematical levels. The purpose of this book is to provide some applications of Bayesian optimization and dynamic programming.

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Dynamic Programming and Bayesian InferenceConcepts and ApplicationsEdited by Mohammad Saber Fallah Nezhad

Published: April 29th 2014

DOI: 10.5772/57005

ISBN: 978-953-51-1364-5

eBook (PDF) ISBN: 978-953-51-5048-0

Copyright year: 2014

Books open for chapter submissions

10073 Total Chapter Downloads

4 Crossref Citations

5 Web of Science Citations

8 Dimensions Citations


Open access peer-reviewed

1. Bayesian Networks for Supporting Model Based Predictive Control of Smart Buildings

By Alessandro Carbonari, Massimo Vaccarini and Alberto Giretti


Open access peer-reviewed

2. Integration of Remotely Sensed Images and Electromagnetic Models into a Bayesian Approach for Soil Moisture Content Retrieval: Methodology and Effect of Prior Information

By Claudia Notarnicola and Romina Solorza


Open access peer-reviewed

3. Optimizing Basel III Liquidity Coverage Ratios

By J. Mukuddem-Petersen, M.A. Petersen and M.P. Mulaudzi


Open access peer-reviewed

4. Risk-Constrained Forward Trading Optimization by Stochastic Approximate Dynamic Programming

By Miguel Gil-Pugliese and Fernando Olsina


Open access peer-reviewed

5. Using Dynamic Programming Based on Bayesian Inference in Selection Problems

By Mohammad Saber Fallah Nezhad


Edited Volume and chapters are indexed in

  • Worldcat
  • OpenAIRE
  • Google Scholar
  • AZ ebsco
  • Base
  • CNKI

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