April 13, 2021

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Stochastic Modelling in Process Technology

Stochastic Modelling in Process Technology
Author : Herold G. Dehling,Timo Gottschalk,Alex C. Hoffmann
Publisher : Elsevier
Release Date : 2007-07-03
Category : Mathematics
Total pages :290
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There is an ever increasing need for modelling complex processes reliably. Computational modelling techniques, such as CFD and MD may be used as tools to study specific systems, but their emergence has not decreased the need for generic, analytical process models. Multiphase and multicomponent systems, and high-intensity processes displaying a highly complex behaviour are becoming omnipresent in the processing industry. This book discusses an elegant, but little-known technique for formulating process models in process technology: stochastic process modelling. The technique is based on computing the probability distribution for a single particle's position in the process vessel, and/or the particle's properties, as a function of time, rather than - as is traditionally done - basing the model on the formulation and solution of differential conservation equations. Using this technique can greatly simplify the formulation of a model, and even make modelling possible for processes so complex that the traditional method is impracticable. Stochastic modelling has sporadically been used in various branches of process technology under various names and guises. This book gives, as the first, an overview of this work, and shows how these techniques are similar in nature, and make use of the same basic mathematical tools and techniques. The book also demonstrates how stochastic modelling may be implemented by describing example cases, and shows how a stochastic model may be formulated for a case, which cannot be described by formulating and solving differential balance equations. Introduction to stochastic process modelling as an alternative modelling technique Shows how stochastic modelling may be succesful where the traditional technique fails Overview of stochastic modelling in process technology in the research literature Illustration of the principle by a wide range of practical examples In-depth and self-contained discussions Points the way to both mathematical and technological research in a new, rewarding field

Stochastic Modelling for Systems Biology, Second Edition

Stochastic Modelling for Systems Biology, Second Edition
Author : Darren J. Wilkinson
Publisher : CRC Press
Release Date : 2011-11-09
Category : Mathematics
Total pages :363
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Since the first edition of Stochastic Modelling for Systems Biology, there have been many interesting developments in the use of "likelihood-free" methods of Bayesian inference for complex stochastic models. Re-written to reflect this modern perspective, this second edition covers everything necessary for a good appreciation of stochastic kinetic modelling of biological networks in the systems biology context. Keeping with the spirit of the first edition, all of the new theory is presented in a very informal and intuitive manner, keeping the text as accessible as possible to the widest possible readership. New in the Second Edition All examples have been updated to Systems Biology Markup Language Level 3 All code relating to simulation, analysis, and inference for stochastic kinetic models has been re-written and re-structured in a more modular way An ancillary website provides links, resources, errata, and up-to-date information on installation and use of the associated R package More background material on the theory of Markov processes and stochastic differential equations, providing more substance for mathematically inclined readers Discussion of some of the more advanced concepts relating to stochastic kinetic models, such as random time change representations, Kolmogorov equations, Fokker-Planck equations and the linear noise approximation Simple modelling of "extrinsic" and "intrinsic" noise An effective introduction to the area of stochastic modelling in computational systems biology, this new edition adds additional mathematical detail and computational methods that will provide a stronger foundation for the development of more advanced courses in stochastic biological modelling.

Software Process Technology

Software Process Technology
Author : Anonim
Publisher : Unknown
Release Date : 1995
Category : Computer software
Total pages :129
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Stochastic Modelling of Electricity and Related Markets

Stochastic Modelling of Electricity and Related Markets
Author : Fred Espen Benth,Jurate Saltyte Benth,Steen Koekebakker
Publisher : World Scientific
Release Date : 2008
Category : Technology & Engineering
Total pages :337
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The markets for electricity, gas and temperature have distinctive features, which provide the focus for countless studies. For instance, electricity and gas prices may soar several magnitudes above their normal levels within a short time due to imbalances in supply and demand, yielding what is known as spikes in the spot prices. The markets are also largely influenced by seasons, since power demand for heating and cooling varies over the year. The incompleteness of the markets, due to nonstorability of electricity and temperature as well as limited storage capacity of gas, makes spot-forward hedging impossible. Moreover, futures contracts are typically settled over a time period rather than at a fixed date. All these aspects of the markets create new challenges when analyzing price dynamics of spot, futures and other derivatives. This book provides a concise and rigorous treatment on the stochastic modeling of energy markets. OrnsteinOCoUhlenbeck processes are described as the basic modeling tool for spot price dynamics, where innovations are driven by time-inhomogeneous jump processes. Temperature futures are studied based on a continuous higher-order autoregressive model for the temperature dynamics. The theory presented here pays special attention to the seasonality of volatility and the Samuelson effect. Empirical studies using data from electricity, temperature and gas markets are given to link theory to practice. Sample Chapter(s). A Survey of Electricity and Related Markets (331 KB). Contents: A Survey of Electricity and Related Markets; Stochastic Analysis for Independent Increment Processes; Stochastic Models for the Energy Spot Price Dynamics; Pricing of Forwards and Swaps Based on the Spot Price; Applications to the Gas Markets; Modeling Forwards and Swaps Using the HeathOCoJarrowOCoMorton Approach; Constructing Smooth Forward Curves in Electricity Markets; Modeling of the Electricity Futures Market; Pricing and Hedging of Energy Options; Analysis of Temperature Derivatives. Readership: Researchers in energy and commodity markets, and mathematical finance.

Probability and Stochastic Modeling

Probability and Stochastic Modeling
Author : Vladimir I. Rotar
Publisher : CRC Press
Release Date : 2012-08-25
Category : Mathematics
Total pages :508
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A First Course in Probability with an Emphasis on Stochastic Modeling Probability and Stochastic Modeling not only covers all the topics found in a traditional introductory probability course, but also emphasizes stochastic modeling, including Markov chains, birth-death processes, and reliability models. Unlike most undergraduate-level probability texts, the book also focuses on increasingly important areas, such as martingales, classification of dependency structures, and risk evaluation. Numerous examples, exercises, and models using real-world data demonstrate the practical possibilities and restrictions of different approaches and help students grasp general concepts and theoretical results. The text is suitable for majors in mathematics and statistics as well as majors in computer science, economics, finance, and physics. The author offers two explicit options to teaching the material, which is reflected in "routes" designated by special "roadside" markers. The first route contains basic, self-contained material for a one-semester course. The second provides a more complete exposition for a two-semester course or self-study.

Selected Water Resources Abstracts

Selected Water Resources Abstracts
Author : Anonim
Publisher : Unknown
Release Date : 1978
Category : Water
Total pages :129
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STAR

STAR
Author : Anonim
Publisher : Unknown
Release Date : 1989-12
Category : Aeronautics
Total pages :129
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Markov Processes for Stochastic Modeling

Markov Processes for Stochastic Modeling
Author : Oliver Ibe
Publisher : Newnes
Release Date : 2013-05-22
Category : Mathematics
Total pages :514
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Markov processes are processes that have limited memory. In particular, their dependence on the past is only through the previous state. They are used to model the behavior of many systems including communications systems, transportation networks, image segmentation and analysis, biological systems and DNA sequence analysis, random atomic motion and diffusion in physics, social mobility, population studies, epidemiology, animal and insect migration, queueing systems, resource management, dams, financial engineering, actuarial science, and decision systems. Covering a wide range of areas of application of Markov processes, this second edition is revised to highlight the most important aspects as well as the most recent trends and applications of Markov processes. The author spent over 16 years in the industry before returning to academia, and he has applied many of the principles covered in this book in multiple research projects. Therefore, this is an applications-oriented book that also includes enough theory to provide a solid ground in the subject for the reader. Presents both the theory and applications of the different aspects of Markov processes Includes numerous solved examples as well as detailed diagrams that make it easier to understand the principle being presented Discusses different applications of hidden Markov models, such as DNA sequence analysis and speech analysis.

Stochastic Processes and Models in Operations Research

Stochastic Processes and Models in Operations Research
Author : Anbazhagan, Neelamegam
Publisher : IGI Global
Release Date : 2016-03-24
Category : Business & Economics
Total pages :338
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Decision-making is an important task no matter the industry. Operations research, as a discipline, helps alleviate decision-making problems through the extraction of reliable information related to the task at hand in order to come to a viable solution. Integrating stochastic processes into operations research and management can further aid in the decision-making process for industrial and management problems. Stochastic Processes and Models in Operations Research emphasizes mathematical tools and equations relevant for solving complex problems within business and industrial settings. This research-based publication aims to assist scholars, researchers, operations managers, and graduate-level students by providing comprehensive exposure to the concepts, trends, and technologies relevant to stochastic process modeling to solve operations research problems.

Stochastic Models in Reliability and Maintenance

Stochastic Models in Reliability and Maintenance
Author : Shunji Osaki
Publisher : Springer Science & Business Media
Release Date : 2012-11-02
Category : Mathematics
Total pages :338
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Our daily lives can be maintained by the high-technology systems. Computer systems are typical examples of such systems. We can enjoy our modern lives by using many computer systems. Much more importantly, we have to maintain such systems without failure, but cannot predict when such systems will fail and how to fix such systems without delay. A stochastic process is a set of outcomes of a random experiment indexed by time, and is one of the key tools needed to analyze the future behavior quantitatively. Reliability and maintainability technologies are of great interest and importance to the maintenance of such systems. Many mathematical models have been and will be proposed to describe reliability and maintainability systems by using the stochastic processes. The theme of this book is "Stochastic Models in Reliability and Main tainability. " This book consists of 12 chapters on the theme above from the different viewpoints of stochastic modeling. Chapter 1 is devoted to "Renewal Processes," under which classical renewal theory is surveyed and computa tional methods are described. Chapter 2 discusses "Stochastic Orders," and in it some definitions and concepts on stochastic orders are described and ag ing properties can be characterized by stochastic orders. Chapter 3 is devoted to "Classical Maintenance Models," under which the so-called age, block and other replacement models are surveyed. Chapter 4 discusses "Modeling Plant Maintenance," describing how maintenance practice can be carried out for plant maintenance.

Analytical and Stochastic Modeling Techniques and Applications

Analytical and Stochastic Modeling Techniques and Applications
Author : Khalid Al-Begain,Armin Heindl,Miklos Telek
Publisher : Springer Science & Business Media
Release Date : 2008-05-26
Category : Computers
Total pages :323
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This book constitutes the refereed proceedings of the 15th International Conference on Analytical and Stochastic Modeling Techniques and Applications, ASMTA 2008, held in Nicosia, Cyprus, in June 2008 in conjunction with ECMS 2008, the 22nd European Conference on Modeling and Simulation. The 22 revised full papers presented were carefully reviewed and selected from 55 submissions. The papers are organized in topical sections on traffic modeling, queueing systems, analytical methods and applications, distributions in stochastic modeling, queueing networks, simulation and model checking, as well as wireless networks.

Who's who in Technology Today

Who's who in Technology Today
Author : Anonim
Publisher : Unknown
Release Date : 1981
Category : Engineers
Total pages :129
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Stochastic Modeling of Microstructures

Stochastic Modeling of Microstructures
Author : Kazimierz Sobczyk,David J. Kirkner
Publisher : Springer Science & Business Media
Release Date : 2012-12-06
Category : Mathematics
Total pages :270
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This book is for a general scientific and engineering audience as a guide to current ideas, methods, and models for stochastic modeling of microstructures. It is a reference for professionals in material modeling, mechanical engineering, materials science, chemical, civil, environmental engineering and applied mathematics.

Applied Mechanics Reviews

Applied Mechanics Reviews
Author : Anonim
Publisher : Unknown
Release Date : 1992
Category : Mechanics, Applied
Total pages :129
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Stochastic Modeling of the Rainfall Runoff-process for Nonpoint Source Pollutant Load Estimation

Stochastic Modeling of the Rainfall Runoff-process for Nonpoint Source Pollutant Load Estimation
Author : Michael A. Collins,Roger Ollis Dickey
Publisher : Unknown
Release Date : 1989
Category : Nonpoint source pollution
Total pages :83
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