This pioneering text provides a comprehensive introduction to systems structure, function, and modeling as applied in all fields of science and engineering. Systems understanding is increasingly recognized as a key to a more holistic education and greater problem solving skills, and is also reflected in the trend toward interdisciplinary approaches to research on complex phenomena. While the concepts and components of systems science will continue to be distributed throughout the various disciplines, undergraduate degree programs in systems science are also being developed, including at the authors’ own institutions. However, the subject is approached, systems science as a basis for understanding the components and drivers of phenomena at all scales should be viewed with the same importance as a traditional liberal arts education. Principles of Systems Science contains many graphs, illustrations, side bars, examples, and problems to enhance understanding. From basic principles of organization, complexity, abstract representations, and behavior (dynamics) to deeper aspects such as the relations between information, knowledge, computation, and system control, to higher order aspects such as auto-organization, emergence and evolution, the book provides an integrated perspective on the comprehensive nature of systems. It ends with practical aspects such as systems analysis, computer modeling, and systems engineering that demonstrate how the knowledge of systems can be used to solve problems in the real world. Each chapter is broken into parts beginning with qualitative descriptions that stand alone for students who have taken intermediate algebra. The second part presents quantitative descriptions that are based on pre-calculus and advanced algebra, providing a more formal treatment for students who have the necessary mathematical background. Numerous examples of systems from every realm of life, including the physical and biological sciences, humanities, social sciences, engineering, pre-med and pre-law, are based on the fundamental systems concepts of boundaries, components as subsystems, processes as flows of materials, energy, and messages, work accomplished, functions performed, hierarchical structures, and more. Understanding these basics enables further understanding both of how systems endure and how they may become increasingly complex and exhibit new properties or characteristics. Serves as a textbook for teaching systems fundamentals in any discipline or for use in an introductory course in systems science degree programs Addresses a wide range of audiences with different levels of mathematical sophistication Includes open-ended questions in special boxes intended to stimulate integrated thinking and class discussion Describes numerous examples of systems in science and society Captures the trend towards interdisciplinary research and problem solving
Packed with new material and research, this second edition of George Friedman’s bestselling Constraint Theory remains an invaluable reference for all engineers, mathematicians, and managers concerned with modeling. As in the first edition, this text analyzes the way Constraint Theory employs bipartite graphs and presents the process of locating the “kernel of constraint” trillions of times faster than brute-force approaches, determining model consistency and computational allowability. Unique in its abundance of topological pictures of the material, this book balances left- and right-brain perceptions to provide a thorough explanation of multidimensional mathematical models. Much of the extended material in this new edition also comes from Phan Phan’s PhD dissertation in 2011, titled “Expanding Constraint Theory to Determine Well-Posedness of Large Mathematical Models.” Praise for the first edition: "Dr. George Friedman is indisputably the father of the very powerful methods of constraint theory." --Cornelius T. Leondes, UCLA "Groundbreaking work. ... Friedman's accomplishment represents engineering at its finest. ... The credibility of the theory rests upon the formal proofs which are interspersed among the illuminating hypothetical dialog sequences between manager and analyst, which bring out distinctions that the organization must face, en route to accepting Friedman's work as essential to achieve quality control in developing and applying large models." --John N. Warfield
Deal with information and uncertainty properly and efficientlyusing tools emerging from generalized information theory Uncertainty and Information: Foundations of Generalized InformationTheory contains comprehensive and up-to-date coverage of resultsthat have emerged from a research program begun by the author inthe early 1990s under the name "generalized information theory"(GIT). This ongoing research program aims to develop a formalmathematical treatment of the interrelated concepts of uncertaintyand information in all their varieties. In GIT, as in classicalinformation theory, uncertainty (predictive, retrodictive,diagnostic, prescriptive, and the like) is viewed as amanifestation of information deficiency, while information isviewed as anything capable of reducing the uncertainty. A broadconceptual framework for GIT is obtained by expanding theformalized language of classical set theory to include moreexpressive formalized languages based on fuzzy sets of varioustypes, and by expanding classical theory of additive measures toinclude more expressive non-additive measures of varioustypes. This landmark book examines each of several theories for dealingwith particular types of uncertainty at the following fourlevels: * Mathematical formalization of the conceived type ofuncertainty * Calculus for manipulating this particular type ofuncertainty * Justifiable ways of measuring the amount of uncertainty in anysituation formalizable in the theory * Methodological aspects of the theory With extensive use of examples and illustrations to clarify complexmaterial and demonstrate practical applications, generoushistorical and bibliographical notes, end-of-chapter exercises totest readers' newfound knowledge, glossaries, and an Instructor'sManual, this is an excellent graduate-level textbook, as well as anoutstanding reference for researchers and practitioners who dealwith the various problems involving uncertainty and information. AnInstructor's Manual presenting detailed solutions to all theproblems in the book is available from the Wiley editorialdepartment.
Mathematics for Mechanical Engineers gives mechanical engineers convenient access to the essential problem solving tools that they use each day. It covers applications employed in many different facets of mechanical engineering, from basic through advanced, to ensure that you will easily find answers you need in this handy guide. For the engineer venturing out of familiar territory, the chapters cover fundamentals like physical constants, derivatives, integrals, Fourier transforms, Bessel functions, and Legendre functions. For the experts, it includes thorough sections on the more advanced topics of partial differential equations, approximation methods, and numerical methods, often used in applications. The guide reviews statistics for analyzing engineering data and making inferences, so professionals can extract useful information even with the presence of randomness and uncertainty. The convenient Mathematics for Mechanical Engineers is an indispensable summary of mathematics processes needed by engineers.
Fuzzy sets and fuzzy logic are powerful mathematical tools for modeling and controlling uncertain systems in industry, humanity, and nature; they are facilitators for approximate reasoning in decision making in the absence of complete and precise information. Their role is significant when applied to complex phenomena not easily described by traditional mathematics.The unique feature of the book is twofold: 1) It is the first introductory course (with examples and exercises) which brings in a systematic way fuzzy sets and fuzzy logic into the educational university and college system. 2) It is designed to serve as a basic text for introducing engineers and scientists from various fields to the theory of fuzzy sets and fuzzy logic, thus enabling them to initiate projects and make applications.
This book describes a comprehensive approach to applying systems science formally to the deep analysis of a wide variety of complex systems. Detailed ‘how-to’ examples of the three phases (analysis-modeling-design) of systems science are applied to systems of various types (machines, organic (e.g. ecosystem), and supra-organic (e.g. business organizations and government). The complexity of the global system has reached proportions that seriously challenge our abilities to understand the consequences of our use of technology, modification of natural ecosystems, or even how to govern ourselves. For this reason, complex mathematics is eschewed when simpler structures will suffice, allowing the widest possible audience to apply and benefit from the available tools and concepts of systems science in their own work. The book shows, in detail, how to functionally and structurally deconstruct complex systems using a fundamental language of systems. It shows how to capture the discovered details in a structured knowledge base from which abstract models can be derived for simulation. The knowledge base is also shown to be a basis for generating system design specifications for human-built artifacts, or policy recommendations/policy mechanisms for socio-economic-ecological systems management. The book builds on principles and methods found in the authors’ textbook Principles of Systems Science (co-authored with Michael Kalton), but without prerequisites. It will appeal to a broad audience that deals with complex systems every day, from design engineers to economic and ecological systems managers and policymakers.
This is truly an interdisciplinary book for knowledge workers in business, finance, management and socio-economic sciences based on fuzzy logic. It serves as a guide to and techniques for forecasting, decision making and evaluations in an environment involving uncertainty, vagueness, impression and subjectivity. Traditional modeling techniques, contrary to fuzzy logic, do not capture the nature of complex systems especially when humans are involved. Fuzzy logic uses human experience and judgement to facilitate plausible reasoning in order to reach a conclusion. Emphasis is on applications presented in the 27 case studies including Time Forecasting for Project Management, New Product Pricing, and Control of a Parasit-Pest System.
The rapid changes that have taken place globally on the economic, social and business fronts characterized the 20th century. The magnitude of these changes has formed an extremely complex and unpredictable decision-making framework, which is difficult to model through traditional approaches. The main purpose of this book is to present the most recent advances in the development of innovative techniques for managing the uncertainty that prevails in the global economic and management environments. These techniques originate mainly from fuzzy sets theory. However, the book also explores the integration of fuzzy sets with other decision support and modeling disciplines, such as multicriteria decision aid, neural networks, genetic algorithms, machine learning, chaos theory, etc. The presentation of the advances in these fields and their real world applications adds a new perspective to the broad fields of management science and economics.
A Systems View of Planning: Towards a Theory of the Urban and Regional Planning Process, Second Edition covers theories of the process of town and regional planning. The book discusses physical change and human ecology; the theory of planning; the variety and entropy of systems; and planning as a conceptual system. The text also describes space and spatial planning; goal formulation in planning; exploratory and normative techniques and intuitive methods in projecting the system; and operational models and their underlying theories. Using linear programming and entropy methods; major aspects of evaluation, program budgeting, cost benefit analysis, and matrix methods; and the spatial method for regional planning are also covered. The book tackles the mixed-programming strategy as well. Engineers, architects, farmers, and foresters will find the book invaluable.
The main objective of the Water Framework Directive in the European countries is to achieve a “good status” of all the water bodies, in the integrated management of river basins. In order to assess the impact of improvement measures, water quality models are necessary. During the previous decades the progress in computer technology and computational methods has supported the development of advanced mathematical models for pollutant transport in rivers and streams. This book is intended to provide the fundamental knowledge needed for a deeper understanding of these models and the development of new ones, which will fulfil future quality requirements in water resources management. This book focuses on the fundamentals of computational techniques required in water quality modelling. Advection, dispersion and concentrated sources or sinks of contaminants lead to the formulation of the fundamental differential equation of pollutant transport. Its integration, according to appropriate initial and boundary conditions and with the knowledge of the velocity field, allows for pollutant behaviour to be assessed in the entire water body. An analytical integration is convenient only in one-dimensional approach with considerable simplification. Integration in the numerical field is useful for taking into account particular aspects of water body and pollutants. To ensure their reliability, the models require accurate calibration and validation, based on proper data, taken from direct measurements. In addition, sensitivity and uncertainty analysis are also of utmost importance. All the above items are discussed in detail in the 21 chapters of the book, which is written in a didactic form for professionals and students.
Some recent fuzzy database modeling advances for the non-traditional applications are introduced in this book. The focus is on database models for modeling complex information and uncertainty at the conceptual, logical, physical design levels and from integrity constraints defined on the fuzzy relations. The database models addressed here are; the conceptual data models, including the ExIFO and ExIFO2 data models, the logical database models, including the extended NF2 database model, fuzzy object-oriented database model, and the fuzzy deductive object-oriented database model. Integrity constraints are defined on the fuzzy relations are also addressed. A continuing reason for the limited adoption of fuzzy database systems has been performance. There have been few efforts at defining physical structures that accomodate fuzzy information. A new access structure and data organization for fuzzy information is introduced in this book.
This scholarly introductory treatment explores the fundamentals of modern geostatistics, viewing them as the product of the advancement of the epistemic status of stochastic data analysis. The book's main focus is the Bayesian maximum entropy approach for studying spatiotemporal distributions of natural variables, an approach that offers readers a deeper understanding of the role of geostatistics in improved mathematical models of scientific mapping. Starting with a overview of the uses of spatiotemporal mapping in the natural sciences, the text explores spatiotemporal geometry, the epistemic paradigm, the mathematical formulation of the Bayesian maximum entropy method, and analytical expressions of the posterior operator. Additional topics include uncertainty assessment, single- and multi-point analytical formulations, and popular methods. An innovative contribution to the field of space and time analysis, this volume offers many potential applications in epidemiology, geography, biology, and other fields.
Ordinary and fractional approximations by non-additive integrals, especially by integral approximators of Choquet, Silkret and Sugeno types, are a new trend in approximation theory. These integrals are only subadditive and only the first two are positive linear, and they produce very fast and flexible approximations based on limited data. The author presents both the univariate and multivariate cases. The involved set functions are much weaker forms of the Lebesgue measure and they were conceived to fulfill the needs of economic theory and other applied sciences. The approaches presented here are original, and all chapters are self-contained and can be read independently. Moreover, the book’s findings are sure to find application in many areas of pure and applied mathematics, especially in approximation theory, numerical analysis and mathematical economics (both ordinary and fractional). Accordingly, it offers a unique resource for researchers, graduate students, and for coursework in the above-mentioned fields, and belongs in all science and engineering libraries.
The book focuses on the development of advanced functions for field-based temporal geographical information systems (TGIS). These fields describe natural, epidemiological, economical, and social phenomena distributed across space and time. The book is organized around four main themes: "Concepts, mathematical tools, computer programs, and applications". Chapters I and II review the conceptual framework of the modern TGIS and introduce the fundamental ideas of spatiotemporal modelling. Chapter III discusses issues of knowledge synthesis and integration. Chapter IV presents state-of-the-art mathematical tools of spatiotemporal mapping. Links between existing TGIS techniques and the modern Bayesian maximum entropy (BME) method offer significant improvements in the advanced TGIS functions. Comparisons are made between the proposed functions and various other techniques (e.g., Kriging, and Kalman-Bucy filters). Chapter V analyzes the interpretive features of the advanced TGIS functions, establishing correspondence between the natural system and the formal mathematics which describe it. In Chapters IV and V one can also find interesting extensions of TGIS functions (e.g., non-Bayesian connectives and Fisher information measures). Chapters VI and VII familiarize the reader with the TGIS toolbox and the associated library of comprehensive computer programs. Chapter VIII discusses important applications of TGIS in the context of scientific hypothesis testing, explanation, and decision making.
Since the late 1960s, there has been a revolution in robots and industrial automation, from the design of robots with no computing or sensorycapabilities (first-generation), to the design of robots with limited computational power and feedback capabilities (second-generation), and the design of intelligent robots (third-generation), which possess diverse sensing and decision making capabilities. The development of the theory of intelligent machines has been developed in parallel to the advances in robot design. This theory is the natural outcome of research and development in classical control (1950s), adaptive and learning control (1960s), self-organizing control (1970s) and intelligent control systems (1980s). The theory of intelligent machines involves utilization and integration of concepts and ideas from the diverse disciplines of science, engineering and mathematics, and fields like artificial intelligence, system theory and operations research. The main focus and motivation is to bridge the gap between diverse disciplines involved and bring under a common cover several generic methodologies pertaining to what has been defined as machine intelligence. Intelligent robotic systems are a specific application of intelligent machines. They are complex computer controlled robotic systems equipped with a diverse set of visual and non visual sensors and possess decision making and problem solving capabilities within their domain of operation. Their modeling and control is accomplished via analytical and heuristic methodologies and techniques pertaining to generalized system theory and artificial intelligence. Intelligent Robotic Systems: Theory, Design and Applications, presents and justifies the fundamental concepts and ideas associated with the modeling and analysis of intelligent robotic systems. Appropriate for researchers and engineers in the general area of robotics and automation, Intelligent Robotic Systems is both a solid reference as well as a text for a graduate level course in intelligent robotics/machines.
This book includes constructive approximation theory; it presents ordinary and fractional approximations by positive sublinear operators, and high order approximation by multivariate generalized Picard, Gauss–Weierstrass, Poisson–Cauchy and trigonometric singular integrals. Constructive and Computational Fractional Analysis recently is more and more in the center of mathematics because of their great applications in the real world. In this book, all presented is original work by the author given at a very general level to cover a maximum number of cases in various applications. The author applies generalized fractional differentiation techniques of Riemann–Liouville, Caputo and Canavati types and of fractional variable order to various kinds of inequalities such as of Opial, Hardy, Hilbert–Pachpatte and on the spherical shell. He continues with E. R. Love left- and right-side fractional integral inequalities. They follow fractional Landau inequalities, of left and right sides, univariate and multivariate, including ones for Semigroups. These are developed to all possible directions, and right-side multivariate fractional Taylor formulae are proven for the purpose. It continues with several Gronwall fractional inequalities of variable order. This book results are expected to find applications in many areas of pure and applied mathematics. As such this book is suitable for researchers, graduate students and seminars of the above disciplines, also to be in all science and engineering libraries.
Artificial intelligence and the interrogation game; Scientific method and explanation; Godel's incompleteness theorem; Determinism and uncertainty; Axioms, theorems and formalisation; Creativity; Consciousness and free will; Pragmatics; A theory of signs; Models as automata; The nervous system.
A generalized approach in a systematic way is inevitable to oversee the challenges one may face in the product development stage to acquire the desired output performance under various operating conditions. This book, Modelling, Stability Analysis, and Control of a Buck Converter: Digital Simulation of Buck Regulator Systems in MATLAB®, written and structured to cater to readers of different levels, aims to provide a clear understanding of different aspects of modelling and practical implementation. The operation of the semiconductor switches, switching characteristics of the energy storage elements, stability analysis, state-space approach, transfer function modelling, mathematical modelling, and closed loop control of the buck converter, which are illustrated in this book can be extended to any other similar system independent of complexity. This book: Covers modelling and control of buck converters and provides sufficient understanding to model and control complex systems. Discusses step response, pole-zero maps, Bode and root locus plots for stability analysis, and design of the controller. Explains time response, frequency response, and stability analysis of the resistive-capacitive (R-C), resistive-inductive (R-L), and R-L-C circuits to support the design of the buck converter. Includes simulation and experimental results to demonstrate the effectiveness of closed loop buck regulator systems using proportional (P), integral (I), and P-I controllers to achieve the desired output performance. Provides MATLAB codes, Algorithms, and MATLAB/PSB models to help readers with digital simulation. It is primarily written for senior undergraduate and graduate students, academic researchers, and specialists in the field of electrical and electronics engineering.
In this book, we introduce the parametrized, deformed and general activation function of neural networks. The parametrized activation function kills much less neurons than the original one. The asymmetry of the brain is best expressed by deformed activation functions. Along with a great variety of activation functions, general activation functions are also engaged. Thus, in this book, all presented is original work by the author given at a very general level to cover a maximum number of different kinds of neural networks: giving ordinary, fractional, fuzzy and stochastic approximations. It presents here univariate, fractional and multivariate approximations. Iterated sequential multi-layer approximations are also studied. The functions under approximation and neural networks are Banach space valued.
This book focuses on computational and fractional analysis, two areas that are very important in their own right, and which are used in a broad variety of real-world applications. We start with the important Iyengar type inequalities and we continue with Choquet integral analytical inequalities, which are involved in major applications in economics. In turn, we address the local fractional derivatives of Riemann–Liouville type and related results including inequalities. We examine the case of low order Riemann–Liouville fractional derivatives and inequalities without initial conditions, together with related approximations. In the next section, we discuss quantitative complex approximation theory by operators and various important complex fractional inequalities. We also cover the conformable fractional approximation of Csiszar’s well-known f-divergence, and present conformable fractional self-adjoint operator inequalities. We continue by investigating new local fractional M-derivatives that share all the basic properties of ordinary derivatives. In closing, we discuss the new complex multivariate Taylor formula with integral remainder. Sharing results that can be applied in various areas of pure and applied mathematics, the book offers a valuable resource for researchers and graduate students, and can be used to support seminars in related fields.
The fifth edition includes• for the first time, stunning color photographs throughout• chapters rearranged and grouped to best reflect phylogenetic relationships, with updated numbers of genera and species for each family• updated mammalian structural and functional adaptations, as well as ordinal fossil histories• recent advances in mammalian phylogeny, biogeography, social behavior, and ecology, with 12 new or revised cladograms reflecting current research findings• new breakout boxes on novel or unique aspects of mammals; new work on female post-copulatory mate choice, cooperative behaviors, group defense, and the role of the vomeronasal system• discussions of the current implications of climate change and other anthropogenic factors for mammalsMaintaining the accessible, readable style for which Feldhamer and his coauthors are well known, this new edition of Mammalogy is the authoritative textbook on this amazingly diverse class of vertebrates.
Information is precious. It reduces our uncertainty in making decisions. Knowledge about the outcome of an uncertain event gives the possessor an advantage. It changes the course of lives, nations, and history itself. Information is the food of Maxwell's demon. His power comes from know ing which particles are hot and which particles are cold. His existence was paradoxical to classical physics and only the realization that information too was a source of power led to his taming. Information has recently become a commodity, traded and sold like or ange juice or hog bellies. Colleges give degrees in information science and information management. Technology of the computer age has provided access to information in overwhelming quantity. Information has become something worth studying in its own right. The purpose of this volume is to introduce key developments and results in the area of generalized information theory, a theory that deals with uncertainty-based information within mathematical frameworks that are broader than classical set theory and probability theory. The volume is organized as follows.
This is a study of a method of thinking in the social sciences known as the loop concept. This concept underlies the notions of feedback and circular causality. After tracing its historical roots, the author argues that modern usage of feedback thinking in the social sciences divides into two main lines of development. He makes extensive use of the analysis of citations and texts from many branches of the social sciences to document this split and to trace its development and implications. The presumption underlying this work is that feedback thinking is one of the most penetrating patterns of thought in all social science. Part of the purpose of the text is to illuminate the significance of feedback thinking in social science and social policy - current as well as classical. (Quelle: amazon)
At first glance, this might appear to be a book on mathematics, but it is really intended for the practical engineer who wishes to gain greater control of the multidimensional mathematical models which are increasingly an important part of his environment. Another feature of the book is that it attempts to balance left- and right-brain perceptions; the author has noticed that many graph theory books are disturbingly light on actual topological pictures of their material. One thing that this book is not is a depiction of the Theory of Constraints, as defined by Eliyahu Goldratt in the 1980’s. Constraint Theory was originally defined by the author in his PhD dissertation in 1967 and subsequent papers written over the following decade. It strives to employ more of a mathematical foundation to complexity than the Theory of Constraints. This merely attempts to differentiate this book from Goldratt’s work, not demean his efforts. After all, the main body of work in the field of 1 Systems Engineering is still largely qualitative .
This book has a rather strange history. It began in Spring 1989, thirteen years after our Systems Science Department at SUNY -Binghamton was established, when I was asked by a group of students in our doctoral program to have a meeting with them. The spokesman of the group, Cliff Joslyn, opened our meeting by stating its purpose. I can closely paraphrase what he said: "We called this meeting to discuss with you, as Chairman of the Department, a fundamental problem with our systems science curriculum. In general, we consider it a good curriculum: we learn a lot of concepts, principles, and methodological tools, mathematical, computational, heuristic, which are fundamental to understanding and dealing with systems. And, yet, we learn virtually nothing about systems science itself. What is systems science? What are its historical roots? What are its aims? Where does it stand and where is it likely to go? These are pressing questions to us. After all, aren't we supposed to carry the systems science flag after we graduate from this program? We feel that a broad introductory course to systems science is urgently needed in the curriculum. Do you agree with this assessment?" The answer was obvious and, yet, not easy to give: "I agree, of course, but I do not see how the situation could be alleviated in the foreseeable future.
Thousands of derivatization procedures for HPLC and CE-an essential tool for today's analytical chemist. This valuable reference offers fast and convenient access to derivatization reactions for both HPLC and capillary electrophoresis (CE). Covering a wide variety of compounds from pharmaceutical drugs and biological products to industrial contaminants, it is organized first by functional group and then by individual reagents. Techniques for each functional group are described in sufficient detail that the researcher can replicate procedures without reference to the original publications-saving hours of tedious library research. And because detailed procedures for the same reagent are listed together, it is easy to combine features of different methods and tailor them to fit specific individual requirements. Also available on CD-ROM, Handbook of Derivatization Reactions for HPLC contains fully abstracted and evaluated procedures from more than 1,900 papers, with descriptions of hundreds of reagents. A further 3,000 papers are referenced in bibliographies that are clearly annotated to help analysts identify those sources likely to be most useful. This important new resource will be welcomed by chemists working in pharmaceutical, biomedical, and environmental analysis. Also available on CD-ROM System requirements . . . IBM-compatible PC 486 or better and Windows(r) 3.0 or higher, or Macintosh 68030 processor and System 7 or higher * CD-ROM drive and 8 MB RAM minimum * 5 MB free hard disk space minimum, 30 MB recommended for full installation.
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