Maximum-entropy Models in Science and Engineering
Maximum-entropy Models in Science and Engineering

Author: Jagat Narain Kapur

Publisher: John Wiley & Sons

Published: 1989

Total Pages: 660

ISBN-13: 9788122402162

DOWNLOAD EBOOK

This Is The First Comprehensive Book About Maximum Entropy Principle And Its Applications To A Diversity Of Fields Like Statistical Mechanics, Thermo-Dynamics, Business, Economics, Insurance, Finance, Contingency Tables, Characterisation Of Probability Distributions (Univariate As Well As Multivariate, Discrete As Well As Continuous), Statistical Inference, Non-Linear Spectral Analysis Of Time Series, Pattern Recognition, Marketing And Elections, Operations Research And Reliability Theory, Image Processing, Computerised Tomography, Biology And Medicine. There Are Over 600 Specially Constructed Exercises And Extensive Historical And Bibliographical Notes At The End Of Each Chapter.The Book Should Be Of Interest To All Applied Mathematicians, Physicists, Statisticians, Economists, Engineers Of All Types, Business Scientists, Life Scientists, Medical Scientists, Radiologists And Operations Researchers Who Are Interested In Applying The Powerful Methodology Based On Maximum Entropy Principle In Their Respective Fields.

Bayesian Inference and Maximum Entropy Methods in Science and Engineering
Bayesian Inference and Maximum Entropy Methods in Science and Engineering

Author: Adriano Polpo

Publisher: Springer

Published: 2018-07-14

Total Pages: 304

ISBN-13: 9783319911427

DOWNLOAD EBOOK

These proceedings from the 37th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2017), held in São Carlos, Brazil, aim to expand the available research on Bayesian methods and promote their application in the scientific community. They gather research from scholars in many different fields who use inductive statistics methods and focus on the foundations of the Bayesian paradigm, their comparison to objectivistic or frequentist statistics counterparts, and their appropriate applications. Interest in the foundations of inductive statistics has been growing with the increasing availability of Bayesian methodological alternatives, and scientists now face much more difficult choices in finding the optimal methods to apply to their problems. By carefully examining and discussing the relevant foundations, the scientific community can avoid applying Bayesian methods on a merely ad hoc basis. For over 35 years, the MaxEnt workshops have explored the use of Bayesian and Maximum Entropy methods in scientific and engineering application contexts. The workshops welcome contributions on all aspects of probabilistic inference, including novel techniques and applications, and work that sheds new light on the foundations of inference. Areas of application in these workshops include astronomy and astrophysics, chemistry, communications theory, cosmology, climate studies, earth science, fluid mechanics, genetics, geophysics, machine learning, materials science, medical imaging, nanoscience, source separation, thermodynamics (equilibrium and non-equilibrium), particle physics, plasma physics, quantum mechanics, robotics, and the social sciences. Bayesian computational techniques such as Markov chain Monte Carlo sampling are also regular topics, as are approximate inferential methods. Foundational issues involving probability theory and information theory, as well as novel applications of inference to illuminate the foundations of physical theories, are also of keen interest.

Entropy Theory in Hydrologic Science and Engineering
Entropy Theory in Hydrologic Science and Engineering

Author: Vijay P. Singh

Publisher: McGraw Hill Professional

Published: 2014-09-22

Total Pages: 849

ISBN-13: 0071835474

DOWNLOAD EBOOK

A THOROUGH INTRODUCTION TO ENTROPY THEORY AND ITS APPLICATIONS IN HYDROLOGIC SCIENCE AND ENGINEERING This comprehensive volume addresses basic concepts of entropy theory from a hydrologic engineering perspective. The application of these concepts to a wide range of hydrologic engineering problems is discussed in detail. The book is divided into sections--preliminaries, rainfall and evapotranspiration, subsurface flow, surface flow, and environmental considerations. Helpful equations, solutions, tables, and diagrams are included throughout this practical resource. Entropy Theory in Hydrologic Science and Engineering covers: Introduction to entropy theory Maximum entropy production principle Performance measures Morphological analysis Evaluation and design of sampling and measurement networks Precipitation variability Rainfall frequency distributions Evaluation of precipitation forecasting schemes Assessment of potential water resources availability Evaporation Infiltration Soil moisture Groundwater flow Rainfall-runoff modeling Streamflow simulation Hydrologic frequency analysis Streamflow forecasting River flow regime classification Sediment yield Eco-index

Bayesian Inference and Maximum Entropy Methods in Science and Engineering
Bayesian Inference and Maximum Entropy Methods in Science and Engineering

Author: Kevin H. Knuth

Publisher: American Institute of Physics

Published: 2007-12-06

Total Pages: 512

ISBN-13:

DOWNLOAD EBOOK

This excellent volume considers the methods, applications and even the foundations of a key area of theoretical study. Namely, that of Bayesian probability, entropy and information theory in scientific and engineering applications. The material here has come out of the so-called MaxEnt workshops that for more than 25 years have explored the subject. Application areas include, but are not limited to: astronomy, physics, chemistry, biology, earth science, and engineering.

Entropy and Energy Dissipation in Water Resources
Entropy and Energy Dissipation in Water Resources

Author: V.P. Singh

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 583

ISBN-13: 9401124302

DOWNLOAD EBOOK

Since the landmark contributions of C. E. Shannon in 1948, and those of E. T. Jaynes about a decade later, applications of the concept of entropy and the principle of maximum entropy have proliterated in science and engineering. Recent years have witnessed a broad range of new and exciting developments in hydrology and water resources using the entropy concept. These have encompassed innovative methods for hydrologic network design, transfer of information, flow forecasting, reliability assessment for water distribution systems, parameter estimation, derivation of probability distributions, drainage-network analysis, sediment yield modeling and pollutant loading, bridge-scour analysis, construction of velocity profiles, comparative evaluation of hydrologic models, and so on. Some of these methods hold great promise for advancement of engineering practice, permitting rational alternatives to conventional approaches. On the other hand, the concepts of energy and energy dissipation are being increasingly applied to a wide spectrum of problems in environmental and water resources. Both entropy and energy dissipation have their origin in thermodynamics, and are related concepts. Yet, many of the developments using entropy seem to be based entirely on statistical interpretation and have seemingly little physical content. For example, most of the entropy-related developments and applications in water resources have been based on the information-theoretic interpretation of entropy. We believe if the power of the entropy concept is to be fully realized, then its physical basis has to be established.

Entropy Measures, Maximum Entropy Principle and Emerging Applications
Entropy Measures, Maximum Entropy Principle and Emerging Applications

Author: Karmeshu

Publisher: Springer

Published: 2012-10-01

Total Pages: 300

ISBN-13: 3540362126

DOWNLOAD EBOOK

The last two decades have witnessed an enormous growth with regard to ap plications of information theoretic framework in areas of physical, biological, engineering and even social sciences. In particular, growth has been spectac ular in the field of information technology,soft computing,nonlinear systems and molecular biology. Claude Shannon in 1948 laid the foundation of the field of information theory in the context of communication theory. It is in deed remarkable that his framework is as relevant today as was when he 1 proposed it. Shannon died on Feb 24, 2001. Arun Netravali observes "As if assuming that inexpensive, high-speed processing would come to pass, Shan non figured out the upper limits on communication rates. First in telephone channels, then in optical communications, and now in wireless, Shannon has had the utmost value in defining the engineering limits we face". Shannon introduced the concept of entropy. The notable feature of the entropy frame work is that it enables quantification of uncertainty present in a system. In many realistic situations one is confronted only with partial or incomplete information in the form of moment, or bounds on these values etc. ; and it is then required to construct a probabilistic model from this partial information. In such situations, the principle of maximum entropy provides a rational ba sis for constructing a probabilistic model. It is thus necessary and important to keep track of advances in the applications of maximum entropy principle to ever expanding areas of knowledge.

Linear Inverse Problems: The Maximum Entropy Connection (With Cd-rom)
Linear Inverse Problems: The Maximum Entropy Connection (With Cd-rom)

Author: Henryk Gzyl

Publisher: World Scientific

Published: 2011-02-16

Total Pages: 351

ISBN-13: 9814462160

DOWNLOAD EBOOK

The book describes a useful tool for solving linear inverse problems subject to convex constraints. The method of maximum entropy in the mean automatically takes care of the constraints. It consists of a technique for transforming a large dimensional inverse problem into a small dimensional non-linear variational problem.A variety of mathematical aspects of the maximum entropy method are explored as well.

Bayesian Inference and Maximum Entropy Methods in Science and Engineering
Bayesian Inference and Maximum Entropy Methods in Science and Engineering

Author: Ali Mohammad-Djafari

Publisher: American Inst. of Physics

Published: 2006-12-13

Total Pages: 616

ISBN-13: 9780735403710

DOWNLOAD EBOOK

The MaxEnt workshops are devoted to Bayesian inference and maximum entropy methods in science and engineering. In addition, this workshop included all aspects of probabilistic inference, such as foundations, techniques, algorithms, and applications. All papers have been peer-reviewed.

Reliability-Based Analysis and Design of Structures and Infrastructure
Reliability-Based Analysis and Design of Structures and Infrastructure

Author: Ehsan Noroozinejad Farsangi

Publisher: CRC Press

Published: 2021-09-27

Total Pages: 522

ISBN-13: 1000418065

DOWNLOAD EBOOK

Increasing demand on improving the resiliency of modern structures and infrastructure requires ever more critical and complex designs. Therefore, the need for accurate and efficient approaches to assess uncertainties in loads, geometry, material properties, manufacturing processes, and operational environments has increased significantly. Reliability-based techniques help develop more accurate initial guidance for robust design and help to identify the sources of significant uncertainty in structural systems. Reliability-Based Analysis and Design of Structures and Infrastructure presents an overview of the methods of classical reliability analysis and design most associated with structural reliability. It also introduces more modern methods and advancements, and emphasizes the most useful methods and techniques used in reliability and risk studies, while elaborating their practical applications and limitations rather than detailed derivations. Features: Provides a practical and comprehensive overview of reliability and risk analysis and design techniques. Introduces resilient and smart structures/infrastructure that will lead to more reliable and sustainable societies. Considers loss elimination, risk management and life-cycle asset management as related to infrastructure projects. Introduces probability theory, statistical methods, and reliability analysis methods. Reliability-Based Analysis and Design of Structures and Infrastructure is suitable for researchers and practicing engineers, as well as upper-level students taking related courses in structural reliability analysis and design.