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Author: Ian T. Cameron Publisher: Elsevier ISBN: 0080514928 Category : Technology & Engineering Languages : en Pages : 561
Book Description
Process Modelling and Model Analysis describes the use of models in process engineering. Process engineering is all about manufacturing--of just about anything! To manage processing and manufacturing systematically, the engineer has to bring together many different techniques and analyses of the interaction between various aspects of the process. For example, process engineers would apply models to perform feasibility analyses of novel process designs, assess environmental impact, and detect potential hazards or accidents. To manage complex systems and enable process design, the behavior of systems is reduced to simple mathematical forms. This book provides a systematic approach to the mathematical development of process models and explains how to analyze those models. Additionally, there is a comprehensive bibliography for further reading, a question and answer section, and an accompanying Web site developed by the authors with additional data and exercises. - Introduces a structured modeling methodology emphasizing the importance of the modeling goal and including key steps such as model verification, calibration, and validation - Focuses on novel and advanced modeling techniques such as discrete, hybrid, hierarchical, and empirical modeling - Illustrates the notions, tools, and techniques of process modeling with examples and advances applications
Author: Ian T. Cameron Publisher: Elsevier ISBN: 0080514928 Category : Technology & Engineering Languages : en Pages : 561
Book Description
Process Modelling and Model Analysis describes the use of models in process engineering. Process engineering is all about manufacturing--of just about anything! To manage processing and manufacturing systematically, the engineer has to bring together many different techniques and analyses of the interaction between various aspects of the process. For example, process engineers would apply models to perform feasibility analyses of novel process designs, assess environmental impact, and detect potential hazards or accidents. To manage complex systems and enable process design, the behavior of systems is reduced to simple mathematical forms. This book provides a systematic approach to the mathematical development of process models and explains how to analyze those models. Additionally, there is a comprehensive bibliography for further reading, a question and answer section, and an accompanying Web site developed by the authors with additional data and exercises. - Introduces a structured modeling methodology emphasizing the importance of the modeling goal and including key steps such as model verification, calibration, and validation - Focuses on novel and advanced modeling techniques such as discrete, hybrid, hierarchical, and empirical modeling - Illustrates the notions, tools, and techniques of process modeling with examples and advances applications
Author: Juš Kocijan Publisher: Springer ISBN: 3319210211 Category : Technology & Engineering Languages : en Pages : 281
Book Description
This monograph opens up new horizons for engineers and researchers in academia and in industry dealing with or interested in new developments in the field of system identification and control. It emphasizes guidelines for working solutions and practical advice for their implementation rather than the theoretical background of Gaussian process (GP) models. The book demonstrates the potential of this recent development in probabilistic machine-learning methods and gives the reader an intuitive understanding of the topic. The current state of the art is treated along with possible future directions for research. Systems control design relies on mathematical models and these may be developed from measurement data. This process of system identification, when based on GP models, can play an integral part of control design in data-based control and its description as such is an essential aspect of the text. The background of GP regression is introduced first with system identification and incorporation of prior knowledge then leading into full-blown control. The book is illustrated by extensive use of examples, line drawings, and graphical presentation of computer-simulation results and plant measurements. The research results presented are applied in real-life case studies drawn from successful applications including: a gas–liquid separator control; urban-traffic signal modelling and reconstruction; and prediction of atmospheric ozone concentration. A MATLAB® toolbox, for identification and simulation of dynamic GP models is provided for download.
Author: Andrew F. Hayes Publisher: Guilford Publications ISBN: 146253466X Category : Social Science Languages : en Pages : 714
Book Description
This book has been replaced by Introduction to Mediation, Moderation, and Conditional Process Analysis, Third Edition, ISBN 978-1-4625-4903-0.
Author: Edmund A. Metera Publisher: Createspace Independent Publishing Platform ISBN: 9781724914989 Category : Languages : en Pages : 220
Book Description
[Special Note: If you ordered in early September, please contact www.processmodelingadvisor.com to receive your FREE final-edited copy directly from the author.] Many business process models don't meet expectations. Why? Business analysts, managers, productivity improvement specialists, and consultants who develop process models by trial and error are prone to fail. This is THE only start-to-finish how-to guide for consistently producing high-quality business models. It shows you how to: - Establish or improve your business process modeling competence using the 6-step Universal Process Modeling Procedure. - Perceive, define/normalize any business process or activity using the 4-part Universal Business Process Definition. - Never miss the 3 Basic Business Process Flow elements. - Efficiently elicit process model content using razor-sharp elicitation agendas. - Elicit and model the 10 most common logical process model refinements. - Validate any process model's quality using 5 Universal Process Model Quality Checklists. - Use any process modeling tool at-hand, whether it be white board or process modeling software. Learn more at www.ProcessModelingAdvisor.com
Author: Jan Mendling Publisher: Springer Science & Business Media ISBN: 3540892249 Category : Computers Languages : en Pages : 205
Book Description
Business process modeling plays an important role in the management of business processes. As valuable design artifacts, business process models are subject to quality considerations. The absence of formal errors such as deadlocks is of paramount importance for the subsequent implementation of the process. In his book Jan Mendling develops a framework for the detection of formal errors in business process models and the prediction of error probability based on quality attributes of these models (metrics). He presents a precise description of Event-driven Process Chains (EPCs), their control-flow semantics and a suitable correctness criterion called EPC soundness.
Author: Henrik Leopold Publisher: Springer ISBN: 3319041754 Category : Business & Economics Languages : en Pages : 199
Book Description
Natural language is one of the most important means of human communication. It enables us to express our will, to exchange thoughts and to document our knowledge in written sources. Owing to its substantial role in many facets of human life, technology for automatically analyzing and processing natural language has recently become increasingly important. In fact, natural language processing tools have paved the way for entirely new business opportunities. The goal of this book is to facilitate the automatic analysis of natural language in process models and to employ this analysis for assisting process model stakeholders. Therefore, a technique is defined that automatically recognizes and annotates process model element labels. In addition, this technique is leveraged to support organizations in effectively utilizing their process models in various ways. The book is organized into seven chapters. It starts with an overview of business process management and linguistics and continues with conceptual contributions on parsing and annotating process model elements, with the detection and correction of process model guideline violations, with the generation of natural language from process models and finally ends with the derivation of service candidates from process models.
Author: David Insua Publisher: John Wiley & Sons ISBN: 0470744537 Category : Mathematics Languages : en Pages : 315
Book Description
Bayesian analysis of complex models based on stochastic processes has in recent years become a growing area. This book provides a unified treatment of Bayesian analysis of models based on stochastic processes, covering the main classes of stochastic processing including modeling, computational, inference, forecasting, decision making and important applied models. Key features: Explores Bayesian analysis of models based on stochastic processes, providing a unified treatment. Provides a thorough introduction for research students. Computational tools to deal with complex problems are illustrated along with real life case studies Looks at inference, prediction and decision making. Researchers, graduate and advanced undergraduate students interested in stochastic processes in fields such as statistics, operations research (OR), engineering, finance, economics, computer science and Bayesian analysis will benefit from reading this book. With numerous applications included, practitioners of OR, stochastic modelling and applied statistics will also find this book useful.
Author: Wei Wang Publisher: Springer ISBN: 3030118096 Category : Computers Languages : en Pages : 138
Book Description
This book combines multiple research methods, experiment, survey, and design science, as well as traditional measurements and neurophysiological techniques that can capture a variety of cognitive behaviors in human information processing, providing more solid and comprehended research findings. While the focus of the book is the modelling of process models and rules, the methods and techniques used in this book can also be adopted and applied to broader conceptual modelling research incorporating a variety of notations (e.g. UML, ER diagrams) or ontologies. It is a revised version of the PhD dissertation written by the author at the School of Information Technology and Electrical Engineering of the University of Queensland, Australia. In 2018, the PhD dissertation won the “CAiSE PhD Award,” granted to outstanding PhD theses in the field of information systems engineering.
Author: Rob Davis Publisher: Springer Science & Business Media ISBN: 1447103211 Category : Computers Languages : en Pages : 531
Book Description
This practical book describes the key operations of ARIS Toolset - the market leading Business Process Modelling Tool. Based on his experience of using ARIS in British Telecommunications plc, the author describes practical ways of using the tool. Using screen shots and plenty of practical examples, Rob Davis shows how ARIS can be used to model business processes. Throughout the book Davis provides readers with tips and short-cuts, enabling users to start modelling quickly and effectively. He also provides insights into the ARIS concepts, and tells readers about the benefits and trade-offs of using the tool in alternative ways. Unlike other books, this practical guide tackles issues found in real projects.
Author: Fabian Pittke Publisher: Logos Verlag Berlin GmbH ISBN: 3832542019 Category : Computers Languages : en Pages : 272
Book Description
In the past decades, organizations had to face numerous challenges due to intensifying globalization, shorter innovation cycles and growing IT support. Business process management is seen as a comprehensive approach to address these challenges. For this purpose, business process models are increasingly utilized to document and redesign relevant parts of the organization's business operations. Since organizations tend to have a huge number of such models, analysis techniques are required that ensure the quality of these process models in an automatic fashion. The goal of this doctoral thesis is the development of model refactoring techniques by integrating and applying concepts from the three main branches of theoretical linguistics: syntax, semantics, and pragmatics. The syntactical refactoring technique addresses linguistic issues that arise by expressing process behavior with natural language. The semantic refactoring technique reworks terminology with overlapping and synonymous meaning. The pragmatic refactoring technique provides recommendations for incompletely specified process models. All of the presented techniques have been evaluated with real-world process model repositories from various industries to demonstrate their applicability and efficiency.
Author: Ian T. Cameron
Author: Ian T. Cameron
Author: Juš Kocijan
Author: Andrew F. Hayes
Author: Edmund A. Metera
Author: Jan Mendling
Author: Henrik Leopold
Author: David Insua
Author: Wei Wang
Author: Rob Davis
Author: Fabian Pittke