Everything your students need to succeed. The best Physics series for the new VCE Study Design. Developed by expert Victorian teachers for, VCE students.
This book provides a complete and comprehensive guide to Pyomo (Python Optimization Modeling Objects) for beginning and advanced modelers, including students at the undergraduate and graduate levels, academic researchers, and practitioners. Using many examples to illustrate the different techniques useful for formulating models, this text beautifully elucidates the breadth of modeling capabilities that are supported by Pyomo and its handling of complex real-world applications. In the third edition, much of the material has been reorganized, new examples have been added, and a new chapter has been added describing how modelers can improve the performance of their models. The authors have also modified their recommended method for importing Pyomo. A big change in this edition is the emphasis of concrete models, which provide fewer restrictions on the specification and use of Pyomo models. Pyomo is an open source software package for formulating and solving large-scale optimization problems. The software extends the modeling approach supported by modern AML (Algebraic Modeling Language) tools. Pyomo is a flexible, extensible, and portable AML that is embedded in Python, a full-featured scripting language. Python is a powerful and dynamic programming language that has a very clear, readable syntax and intuitive object orientation. Pyomo includes Python classes for defining sparse sets, parameters, and variables, which can be used to formulate algebraic expressions that define objectives and constraints. Moreover, Pyomo can be used from a command-line interface and within Python's interactive command environment, which makes it easy to create Pyomo models, apply a variety of optimizers, and examine solutions.
This book is intended for specialists as well as students and graduate students in the field of artificial intelligence, robotics and information technology. It is will also appeal to a wide range of readers interested in expanding the functionality of artificial intelligence systems. One of the pressing problems of modern artificial intelligence systems is the development of integrated hybrid systems based on deep learning. Unfortunately, there is currently no universal methodology for developing topologies of hybrid neural networks (HNN) using deep learning. The development of such systems calls for the expansion of the use of neural networks (NS) for solving recognition, classification and optimization problems. As such, it is necessary to create a unified methodology for constructing HNN with a selection of models of artificial neurons that make up HNN, gradually increasing the complexity of their structure using hybrid learning algorithms.
Recent years have witnessed enormous strides in the field of robust control of dynamical systems -- unfortunately, many of these developments have only been accessible to a small group of experts. In this text for students and control engineers, the authors examines all of these advances, providing an in-depth and exhaustive examination of modern optimal and robust control. "--
Robust Industrial Control Systems: Optimal Design Approach for Polynomial Systems presents a comprehensive introduction to the use of frequency domain and polynomial system design techniques for a range of industrial control and signal processing applications. The solution of stochastic and robust optimal control problems is considered, building up from single-input problems and gradually developing the results for multivariable design of the later chapters. In addition to cataloguing many of the results in polynomial systems needed to calculate industrial controllers and filters, basic design procedures are also introduced which enable cost functions and system descriptions to be specified in order to satisfy industrial requirements. Providing a range of solutions to control and signal processing problems, this book: * Presents a comprehensive introduction to the polynomial systems approach for the solution of H_2 and H_infinity optimal control problems. * Develops robust control design procedures using frequency domain methods. * Demonstrates design examples for gas turbines, marine systems, metal processing, flight control, wind turbines, process control and manufacturing systems. * Includes the analysis of multi-degrees of freedom controllers and the computation of restricted structure controllers that are simple to implement. * Considers time-varying control and signal processing problems. * Addresses the control of non-linear processes using both multiple model concepts and new optimal control solutions. Robust Industrial Control Systems: Optimal Design Approach for Polynomial Systems is essential reading for professional engineers requiring an introduction to optimal control theory and insights into its use in the design of real industrial processes. Students and researchers in the field will also find it an excellent reference tool.
Fuzzy controllers are a class of knowledge based controllers using artificial intelligence techniques with origins in fuzzy logic to compute an appropriate control action. These fuzzy knowledge based controllers can be found either as stand-alone control elements or as integral parts of distributed control systems including conventional controllers in a wide range of industrial process control systems and consumer products. Applications of fuzzy controllers have become a well established practice for Japanese manufacturers of control equipment and systems, and are becoming more and more common for their European and American counterparts. The main aim of this book is to show that fuzzy control is not totally ad hoc, that there exist formal techniques for the analysis of a fuzzy controller, and that fuzzy control can be implemented even when no expert knowledge is available. Thus the book is mainly oriented toward control engineers and theorists rather than fuzzy and non-fuzzy AI people. However, parts can be read without any knowledge of control theory and may be of interest to AI people. The book has six chapters. Chapter 1 introduces two major classes of knowledge based systems for closedloop control. Chapter 2 introduces relevant parts of fuzzy set theory and fuzzy logic. Chapter 3 introduces the principal design parameters of a fuzzy knowledge based controller (FKBC) and discusses their relevance with respect to its performance. Chapter 4 considers an FKBC as a particular type of nonlinear controller. Chapter 5 considers tuning and adaptation of FKBCs, which are nonlinear and so can be designed to cope with a certain amount of nonlinearity. Chapter 6 considers several approaches for stability analysis of FKBCs in the context of classical nonlinear dynamic systems theory.
The basic working knowledge for the practicing control engineer in industry, offered here as a handy deluxe edition comprising two volumes each devoted to methods and practical problems. Focusing on the practical implementation, the methods volume provides readers with rapid access to process modelling and control, while including the theoretical background necessary. Throughout, the essential knowledge is built up from chapter to chapter, starting with laying the foundations in plant instrumentation and control. Modelling abilities are then developed by starting from simple time-loop algorithms and passing on to discrete methods, Laplace transforms, automata and fuzzy logic. In the end, readers have the means to design simple controllers on the basis of their own models, and to use more detailed models to test them. With its clarity and simplicity of presentation, and illustrated by more than 200 diagrams, the volume supports self-study and teaches readers how to apply the appropriate method for the application required, and how to handle problems in process control. Bridging theory and practice, the second volume contains over 200 practical exercises and their solutions to develop the problem-solving abilities of process engineers. The problems were developed by the author during his many years of teaching at university and are kept brief, taken from the fields of instrumentation, modeling, plant control, control strategy design and stability of control. The algorithm flows and codes, which are mostly based on MATLAB®, are given in many cases and allow for easy translation into applications. With a clarity and simplicity of presentation, the two volumes are similarly structured for easy orientation.
Stormwater Modeling presents the fundamentals of deterministic, parametric, and stochastic stormwater modeling. It is assumed that the reader or student will have a basic background in science or engineering; however, the authors are of the opinion that one can comfortably read and understand this treatise with a fundamental knowledge of calculus and differential equations. The book has been written with the intent of reaching an audience concerned primarily with evaluating the effects of land use on stormwater for the purpose of doing feasibility studies, planning, and/or design work. The book is organized into five parts. Part I discusses various modeling concepts such as the definition of a mathematical model, the systems approach to model building, examples of parametric and deterministic modeling, and stormwater model optimization. Part II on deterministic modeling covers the modeling of overland and open channel flow; kinematic flow approximation; and estimation of time of concentration using kinematic wave theory. Part III covers parametric modeling and includes chapters on model optimization;. analysis of the effects of urbanization and logging on stormwater; and evaluation of the effects of strip coal mining on watershed hydrologic response. Parts IV and V deal with stochastic stormwater modeling and stormwater quality modeling, respectively.
Learn to apply modeling and parameter estimation tools and strategies to chemicalprocesses using your personal computer This book introduces readers to powerful parameter estimation and computational methods for modeling complex chemical reactions and reaction processes. It presents useful mathematical models, numerical methods for solving them, and statistical methods for testing and discriminating candidate models with experimental data. Topics covered include: Chemical reaction models Chemical reactor models Probability and statistics Bayesian estimation Process modeling with single-response data Process modeling with multi-response data Computer software (Athena Visual Studio) is available via a related Web site http://www.athenavisual.com enabling readers to carry out parameter estimation based on their data and to carry out process modeling using these parameters. As an aid to the reader, an appendix of example problems and solutions is provided. Computer-Aided Modeling of Reactive Systems is an ideal supplemental text for advanced undergraduates and graduate students in chemical engineering courses, while it also serves as a valuable resource for practitioners in industry who want to keep up to date on the most current tools and strategies available.
Operations Research: A Practical Introduction is just that: a hands-on approach to the field of operations research (OR) and a useful guide for using OR techniques in scientific decision making, design, analysis and management. The text accomplishes two goals. First, it provides readers with an introduction to standard mathematical models and algorithms. Second, it is a thorough examination of practical issues relevant to the development and use of computational methods for problem solving. Highlights: All chapters contain up-to-date topics and summaries A succinct presentation to fit a one-term course Each chapter has references, readings, and list of key terms Includes illustrative and current applications New exercises are added throughout the text Software tools have been updated with the newest and most popular software Many students of various disciplines such as mathematics, economics, industrial engineering and computer science often take one course in operations research. This book is written to provide a succinct and efficient introduction to the subject for these students, while offering a sound and fundamental preparation for more advanced courses in linear and nonlinear optimization, and many stochastic models and analyses. It provides relevant analytical tools for this varied audience and will also serve professionals, corporate managers, and technical consultants.
Introducing engineering students to numerical analysis and computing, this book covers a range of topics suitable for the first three years of a four year undergraduate engineering degree. The teaching of computing to engineers is hampered by the lack of suitable problems for the students to tackle, so much effort has gone into making the problems in this book realistic and relevant, while at the same time solvable for undergraduates. Taking a balanced approach to teaching computing and computer methods at the same time, this book satisfies the need to be able to use computers (using both formal languages such as Fortran and other applications such as Matlab and Microsoft Excel), and the need to be able to solve realistic engineering problems.
Students with diverse backgrounds will face a multitude of decisions in a variety of engineering, scientific, industrial, and financial settings. They will need to know how to identify problems that the methods of operations research (OR) can solve, how to structure the problems into standard mathematical models, and finally how to apply or develop computational tools to solve the problems. Perfect for any one-semester course in OR, Operations Research: A Practical Introduction answers all of these needs. In addition to providing a practical introduction and guide to using OR techniques, it includes a timely examination of innovative methods and practical issues related to the development and use of computer implementations. It provides a sound introduction to the mathematical models relevant to OR and illustrates the effective use of OR techniques with examples drawn from industrial, computing, engineering, and business applications Many students will take only one course in the techniques of Operations Research. Operations Research: A Practical Introduction offers them the greatest benefit from that course through a broad survey of the techniques and tools available for quantitative decision making. It will also encourage other students to pursue more advanced studies and provides you a concise, well-structured, vehicle for delivering the best possible overview of the discipline.
A valuable addition to the Wiley Series in Microwave and Optical Engineering Today's modern wireless mobile communications depend on adaptive "smart" antennas to provide maximum range and clarity. With the recent explosive growth of wireless applications, smart antenna technology has achieved widespread commercial and military applications. The only book available on the topic of adaptive antennas using digital technology, this text reflects the latest developments in smart antenna technology and offers timely information on fundamentals, as well as new adaptive techniques developed by the authors. Coupling electromagnetic aspects of antenna design with signal processing techniques designed to promote accurate and efficient information exchange, the text presents various mechanisms for characterizing signal-path loss associated with signal propagation, particularly for mobile wireless communications systems based on such techniques as joint space-frequency adaptive processing. In clear, accessible language, the authors: * explain the difference between adaptive antennas and adaptive signal processing * Illustrate the procedures for adaptive processing using directive elements in a conformal array * clarify multistage analysis procedure which combines electromagnetic analysis with signal processing * present a survey of the various models for characterizing radio wave propagation in urban and rural environments * describe a method wherein it is possible to identify and eliminate multipath without spatial diversity * optimize the location of base stations in a complex environment The text is an excellent resource for researchers and engineers working in electromagnetics and signal processing who deal with performance improvement of adaptive techniques, as well as those who are concerned with the characterization of propagation channels and applications of airborne phased arrays.
Leadership: A Communication Perspective has been at the forefront of university and college leadership courses for nearly three decades, providing a compelling, authoritative introduction to leadership as a communication-based activity. The new edition continues the tradition of excellence with an up-to-date treatment of theory and research combined with practical, real-world advice for improving communication competence and leadership effectiveness. Relevant: The authors profile contemporary leaders and organizations like Alibaba’s Jack Ma, Zappos’ Tony Hsieh, Facebook’s Sheryl Sandberg, Uber, The Container Store, Airbnb, Chipotle, the Waffle House, Nordstrom, and Google. Their presentation balances current scholarship and trends with historical perspectives to provide a fuller understanding of the study and practice of leadership. Comprehensive: Leadership and followership are examined in multiple contexts, including organizational leadership, public leadership, and leadership in groups and teams. Topics new to this edition include transcendent followership, the leadership skills approach, team coaching, escalation of commitment, invisible leadership, cultural intelligence, trigger events, and resilience. Full-featured: Self-Assessments measure readers’ perceptions of personal leadership skills, communication style, cultural intelligence, motivation to lead, and more. Case Studies examine leadership situations and pose thoughtful questions that prompt students to apply their experiences and understandings. Research Highlights summarize seminal and recent scholarship. Chapter Takeaways reinforce important concepts and action steps. Application Exercises offer abundant opportunities to explore, practice, and reflect on chapter content. Cultural Connections discuss leadership expectations and behaviors in other cultures. Leadership on the Big Screen correlates chapter concepts with the themes of popular films and documentaries.
This book is concerned with the management of organisational change. It focuses on Cadbury Ltd and provides an in-depth study of change within this famous British company. Cadbury Ltd is famous for its pioneering personnel management. One of the purposes of this study is to assess how this established company ethos facilitated change by examining the development and implementation of a capital investment programme that radically changed working practices at the company's Bournville plant in Birmingham. At a more general level the authors develop a theory of organisational change that emphasises the interaction between external market forces and internal management action. This approach unites an emphasis on the structural parameters that limit a firm's capacity for independent change, with a recognition of the vital role performed by influential members of an organisation in initiating and managing change. This book will be of interest to teachers and students of business history, organisational behaviour, industrial relations and industrial sociology.
Michael Goller gives a structured overview of the current discourses of human agency in relation to professional learning and development. Based on this discussion, the author develops a theoretical framework including human agency as an individual feature (i. e., a disposition) as well as a set of self-initiated and goal-directed behaviours that are assumed to affect employees’ learning and development (e. g., crafting of new work experiences). He then further specifies this theoretical framework and investigates it empirically in the domain of geriatric care nursing. Based on the findings of the three empirical studies conducted, the author discusses the relevance of human agency for the development of professional expertise of geriatric care nurses. The work received the American Educational Research Association (AERA) Workplace Learning SIG 2017 Dissertation of the Year Award.
Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications discusses algorithmic developments in the context of genetic algorithms (GAs) and genetic programming (GP). It applies the algorithms to significant combinatorial optimization problems and describes structure identification using HeuristicLab as a platform for al
Country practices towards managing financial risks on a sovereign balance sheet continue to evolve. Each crisis period, and its legacy on sovereign balance sheets, reaffirms the need for strengthening financial risk management. This paper discusses some salient features embedded in in the current generation of sovereign asset and liability management (SALM) approaches, including objectives, definitions of relevant assets and liabilities, and methodologies used in obtaining optimal SALM outcomes. These elements are used in developing an analytical SALM framework which could become an operational instrument in formulating asset management and debtor liability management strategies at the sovereign level. From a portfolio perspective, the SALM approach could help detect direct and derived sovereign risk exposures. It allows analyzing the financial characteristics of the balance sheet, identifying sources of costs and risks, and quantifying the correlations among these sources of risk. The paper also outlines institutional requirements in implementing an SALM framework and seeks to lay the ground for further policy and analytical work on this topic.
If we don’t get Sunday right, we won’t get Monday—or any day of the workweek—right. The divided life is a temptation so built into our society, we may not even recognize it. Yet most of us fall prey to it. We either undervalue work, resenting it as simply a job, or we overvalue it as an identity-defining career. Michael Naughton, drawing on his background in both business and theology, proposes that the key to finding balance is another important human activity: leisure. In light of leisure—not mere amusement, but time for family, silence, prayer, and above all, worship—work becomes a space where men and women can find deep fulfilment. Naughton provides real-world examples of how businesses can promote authentic human flourishment and innovation through practices and policies that support leisure. In Getting Work Right Michael Naughton will change how you work—and rest.
This book is intended to meet the needs of those who seek to develop control systems for ROVs when there is no model available during the initial design stage. The modeling, simulation and application of marine vehicles like underwater robotic vehicles (URVs) are multidisciplinary, and combine mathematical aspects from various engineering disciplines. URVs such as remotely operated vehicle (ROVs) are used for a wide range of applications such as exploring the extreme depths of our ocean, where a hard-wired link is still required. Most ROVs operate in extreme environments with uncertainties in the model prior to control system design. However, the method involved extensive testing before the system model could be used for any control actions. It has been found that the range of error can be extensive and uncertain in actual, continuously varying conditions. Hence, it is important to address the problem of reliance on model testing using different modeling approaches. In this book, approaches such as WAMIT, ANSYS-CFX, STAR CCM+, MATLAB and Simulink are used to model parameters for ROVs. A few benchmark models are provided, allowing researchers and students to explore and test different control schemes. Given its scope, the book offers a valuable reference guide for postgraduate and undergraduate students engaged in modeling and simulation for ROV control.
This book differs from traditional numerical analysis texts in that it focuses on the motivation and ideas behind the algorithms presented rather than on detailed analyses of them. It presents a broad overview of methods and software for solving mathematical problems arising in computational modeling and data analysis, including proper problem formulation, selection of effective solution algorithms, and interpretation of results.? In the 20 years since its original publication, the modern, fundamental perspective of this book has aged well, and it continues to be used in the classroom. This Classics edition has been updated to include pointers to Python software and the Chebfun package, expansions on barycentric formulation for Lagrange polynomial interpretation and stochastic methods, and the availability of about 100 interactive educational modules that dynamically illustrate the concepts and algorithms in the book. Scientific Computing: An Introductory Survey, Second Edition is intended as both a textbook and a reference for computationally oriented disciplines that need to solve mathematical problems.
Converse Lyapunov function theory guarantees the existence of strict Lyapunov functions in many situations, but the functions it provides are often abstract and nonexplicit, and therefore may not lend themselves to engineering applications. Often, even when a system is known to be stable, one still needs explicit Lyapunov functions; however, once an appropriate strict Lyapunov function has been constructed, many robustness and stabilization problems can be solved through standard feedback designs or robustness arguments. Non-strict Lyapunov functions are often readily constructed. This book contains a broad repertoire of Lyapunov constructions for nonlinear systems, focusing on methods for transforming non-strict Lyapunov functions into strict ones. Their explicitness and simplicity make them suitable for feedback design, and for quantifying the effects of uncertainty. Readers will benefit from the authors’ mathematical rigor and unifying, design-oriented approach, as well as the numerous worked examples.
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