Simultaneous Gross Error Detection And Data Reconciliation Using Gaussian Mixture Distribution
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Simultaneous Gross Error Detection And Data Reconciliation Using Gaussian Mixture Distribution
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Author : Hashem Alighardashi
language : en
Publisher:
Release Date : 2017
Simultaneous Gross Error Detection And Data Reconciliation Using Gaussian Mixture Distribution written by Hashem Alighardashi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Errors, Scientific categories.
The intensive competitive nature of the world market, the growing significance of quality products, and the increasing importance and the number of safety and environmental issues and regulations, respectively, have increased the need for fast and low-cost changes in chemical processes to enhance their performance. Any possible changes and modifications in a system in order to control, optimize, evaluate the behavior of the process, or achieve the maximal performance of the system require clear understanding and knowledge of its actual state. This information is obtained by processing a data set - collecting it, ameliorating its accuracy, and storing/using it for further analysis. It should be emphasized that in today's highly competitive world market, increasing the accuracy of measurements by resolving even small errors can result in substantial improvements in plant efficiency and economy. Industrial process measurements play a significant role in online optimization, process monitoring, identification, and control. These measurements are used to make decisions which potentially influence product quality, plant safety, and profitability. Nonetheless, they are inherently contaminated by errors, which may be random and/or systematic/gross errors, due to sensor accuracy, improper instrumentation, poor calibration, process leak, and so on. The objective of data reconciliation and gross error detection is the estimation of the true states and the detection of any faults in the instruments which could seriously degrade the performance of the system. Data reconciliation techniques deal with the problem of improving the accuracy of raw process measurements and their application allows optimal adjustment of measurement values to satisfy material and energy constraints. These methods also make possible estimation of the unmeasured variables. However, data reconciliation approaches do not always provide valid estimates of the actual states, and the presence of gross errors in the measurements significantly affect the accuracy levels that can be accomplished using reconciliation. Therefore, the main focus of this work is to develop a framework to obtain the accurate estimates of reconciled values while reducing the impact of gross errors. In reality, operating conditions under which a process works change with different circumstances. Therefore, it is vital to develop a model that is capable of identifying and switching between operating regions. To this end, a method is proposed for simultaneous gross error detection and rectification of a data set which contains different operating regions. First, the data set is divided into several clusters based on the number of operating regions. Then, the same operation, i.e., data rectification is performed on each operating region. It must be noted that all of the proposed approaches in this thesis do not require to preset the parameters of the error distribution model, rather they are determined as part of the solution. They are also applicable to problems with both linear and nonlinear constraints, in addition to the ability to determine the magnitude of gross errors. Furthermore, these methods/approaches detect partial gross errors, so it is not required to assume that gross errors exist in the entire data set. Finally, the performance of the proposed methods is verified through various simulation studies and realistic examples.
Data Reconciliation And Gross Error Detection
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Author : Shankar Narasimhan
language : en
Publisher: Elsevier
Release Date : 1999-11-29
Data Reconciliation And Gross Error Detection written by Shankar Narasimhan and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-11-29 with Business & Economics categories.
This book provides a systematic and comprehensive treatment of the variety of methods available for applying data reconciliation techniques. Data filtering, data compression and the impact of measurement selection on data reconciliation are also exhaustively explained.Data errors can cause big problems in any process plant or refinery. Process measurements can be correupted by power supply flucutations, network transmission and signla conversion noise, analog input filtering, changes in ambient conditions, instrument malfunctioning, miscalibration, and the wear and corrosion of sensors, among other factors. Here's a book that helps you detect, analyze, solve, and avoid the data acquisition problems that can rob plants of peak performance. This indispensable volume provides crucial insights into data reconciliation and gorss error detection techniques that are essential fro optimal process control and information systems. This book is an invaluable tool for engineers and managers faced with the selection and implementation of data reconciliation software, or for those developing such software. For industrial personnel and students, Data Reconciliation and Gross Error Detection is the ultimate reference.
Data Processing And Reconciliation For Chemical Process Operations
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Author : José A. Romagnoli
language : en
Publisher: Elsevier
Release Date : 1999-10-25
Data Processing And Reconciliation For Chemical Process Operations written by José A. Romagnoli and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-10-25 with Technology & Engineering categories.
Computer techniques have made online measurements available at every sampling period in a chemical process. However, measurement errors are introduced that require suitable techniques for data reconciliation and improvements in accuracy. Reconciliation of process data and reliable monitoring are essential to decisions about possible system modifications (optimization and control procedures), analysis of equipment performance, design of the monitoring system itself, and general management planning. While the reconciliation of the process data has been studied for more than 20 years, there is no single source providing a unified approach to the area with instructions on implementation. Data Processing and Reconciliation for Chemical Process Operations is that source. Competitiveness on the world market as well as increasingly stringent environmental and product safety regulations have increased the need for the chemical industry to introduce such fast and low cost improvements in process operations. - Introduces the first unified approach to this important field - Bridges theory and practice through numerous worked examples and industrial case studies - Provides a highly readable account of all aspects of data classification and reconciliation - Presents the reader with material, problems, and directions for further study
A User S Guide To Principal Components
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Author : J. Edward Jackson
language : en
Publisher: John Wiley & Sons
Release Date : 2005-01-21
A User S Guide To Principal Components written by J. Edward Jackson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-01-21 with Mathematics categories.
WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. From the Reviews of A User’s Guide to Principal Components "The book is aptly and correctly named–A User’s Guide. It is the kind of book that a user at any level, novice or skilled practitioner, would want to have at hand for autotutorial, for refresher, or as a general-purpose guide through the maze of modern PCA." –Technometrics "I recommend A User’s Guide to Principal Components to anyone who is running multivariate analyses, or who contemplates performing such analyses. Those who write their own software will find the book helpful in designing better programs. Those who use off-the-shelf software will find it invaluable in interpreting the results." –Mathematical Geology
Process Modelling And Simulation
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Author : César de Prada
language : en
Publisher: MDPI
Release Date : 2019-09-23
Process Modelling And Simulation written by César de Prada and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-23 with Technology & Engineering categories.
Since process models are nowadays ubiquitous in many applications, the challenges and alternatives related to their development, validation, and efficient use have become more apparent. In addition, the massive amounts of both offline and online data available today open the door for new applications and solutions. However, transforming data into useful models and information in the context of the process industry or of bio-systems requires specific approaches and considerations such as new modelling methodologies incorporating the complex, stochastic, hybrid and distributed nature of many processes in particular. The same can be said about the tools and software environments used to describe, code, and solve such models for their further exploitation. Going well beyond mere simulation tools, these advanced tools offer a software suite built around the models, facilitating tasks such as experiment design, parameter estimation, model initialization, validation, analysis, size reduction, discretization, optimization, distributed computation, co-simulation, etc. This Special Issue collects novel developments in these topics in order to address the challenges brought by the use of models in their different facets, and to reflect state of the art developments in methods, tools and industrial applications.
Ai And Learning Systems
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Author : Konstantinos Kyprianidis
language : en
Publisher: BoD – Books on Demand
Release Date : 2021-02-17
Ai And Learning Systems written by Konstantinos Kyprianidis and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-17 with Technology & Engineering categories.
Over the last few years, interest in the industrial applications of AI and learning systems has surged. This book covers the recent developments and provides a broad perspective of the key challenges that characterize the field of Industry 4.0 with a focus on applications of AI. The target audience for this book includes engineers involved in automation system design, operational planning, and decision support. Computer science practitioners and industrial automation platform developers will also benefit from the timely and accurate information provided in this work. The book is organized into two main sections comprising 12 chapters overall: •Digital Platforms and Learning Systems •Industrial Applications of AI
Current Index To Statistics Applications Methods And Theory
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Author :
language : en
Publisher:
Release Date : 1990
Current Index To Statistics Applications Methods And Theory written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Mathematical statistics categories.
The Current Index to Statistics (CIS) is a bibliographic index of publications in statistics, probability, and related fields.
How I Became A Quant
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Author : Richard R. Lindsey
language : en
Publisher: John Wiley & Sons
Release Date : 2011-01-11
How I Became A Quant written by Richard R. Lindsey and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-11 with Business & Economics categories.
Praise for How I Became a Quant "Led by two top-notch quants, Richard R. Lindsey and Barry Schachter, How I Became a Quant details the quirky world of quantitative analysis through stories told by some of today's most successful quants. For anyone who might have thought otherwise, there are engaging personalities behind all that number crunching!" --Ira Kawaller, Kawaller & Co. and the Kawaller Fund "A fun and fascinating read. This book tells the story of how academics, physicists, mathematicians, and other scientists became professional investors managing billions." --David A. Krell, President and CEO, International Securities Exchange "How I Became a Quant should be must reading for all students with a quantitative aptitude. It provides fascinating examples of the dynamic career opportunities potentially open to anyone with the skills and passion for quantitative analysis." --Roy D. Henriksson, Chief Investment Officer, Advanced Portfolio Management "Quants"--those who design and implement mathematical models for the pricing of derivatives, assessment of risk, or prediction of market movements--are the backbone of today's investment industry. As the greater volatility of current financial markets has driven investors to seek shelter from increasing uncertainty, the quant revolution has given people the opportunity to avoid unwanted financial risk by literally trading it away, or more specifically, paying someone else to take on the unwanted risk. How I Became a Quant reveals the faces behind the quant revolution, offering you?the?chance to learn firsthand what it's like to be a?quant today. In this fascinating collection of Wall Street war stories, more than two dozen quants detail their roots, roles, and contributions, explaining what they do and how they do it, as well as outlining the sometimes unexpected paths they have followed from the halls of academia to the front lines of an investment revolution.
26th European Symposium On Computer Aided Process Engineering
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Author :
language : en
Publisher: Elsevier
Release Date : 2016-06-17
26th European Symposium On Computer Aided Process Engineering written by and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-17 with Computers categories.
26th European Symposium on Computer Aided Process Engineering contains the papers presented at the 26th European Society of Computer-Aided Process Engineering (ESCAPE) Event held at Portorož Slovenia, from June 12th to June 15th, 2016. Themes discussed at the conference include Process-product Synthesis, Design and Integration, Modelling, Numerical analysis, Simulation and Optimization, Process Operations and Control and Education in CAPE/PSE. - Presents findings and discussions from the 26th European Society of Computer-Aided Process Engineering (ESCAPE) Event
Bayesian Networks
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Author : Olivier Pourret
language : en
Publisher: John Wiley & Sons
Release Date : 2008-04-30
Bayesian Networks written by Olivier Pourret and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-30 with Mathematics categories.
Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are growing in popularity. Their versatility and modelling power is now employed across a variety of fields for the purposes of analysis, simulation, prediction and diagnosis. This book provides a general introduction to Bayesian networks, defining and illustrating the basic concepts with pedagogical examples and twenty real-life case studies drawn from a range of fields including medicine, computing, natural sciences and engineering. Designed to help analysts, engineers, scientists and professionals taking part in complex decision processes to successfully implement Bayesian networks, this book equips readers with proven methods to generate, calibrate, evaluate and validate Bayesian networks. The book: Provides the tools to overcome common practical challenges such as the treatment of missing input data, interaction with experts and decision makers, determination of the optimal granularity and size of the model. Highlights the strengths of Bayesian networks whilst also presenting a discussion of their limitations. Compares Bayesian networks with other modelling techniques such as neural networks, fuzzy logic and fault trees. Describes, for ease of comparison, the main features of the major Bayesian network software packages: Netica, Hugin, Elvira and Discoverer, from the point of view of the user. Offers a historical perspective on the subject and analyses future directions for research. Written by leading experts with practical experience of applying Bayesian networks in finance, banking, medicine, robotics, civil engineering, geology, geography, genetics, forensic science, ecology, and industry, the book has much to offer both practitioners and researchers involved in statistical analysis or modelling in any of these fields.