Systems Evaluation, Prediction, and Decision-Making – serie

Extension innovation method is an approach to originality generation. It utilizes basic theories of Extenics, a new discipline for modeling contradiction problems with formalized methods and transformation, to establish a modeling and quantification combined method that can be learned effortlessly and operated conveniently. This book introduces and analyzes commonly used extension innovation methods are introduced and analyzed thoroughly. It makes it easy for readers at different levels and of different knowledge backgrounds to study. Highly accessible cases faciliate understanding and application of the models.

A book in the Systems Evaluation, Prediction, and Decision-Making Series, Systems Evaluation: Methods, Models, and Applications covers the evolutionary course of systems evaluation methods, clearly and concisely. Outlining a wide range of methods and models, it begins by examining the method of qualitative assessment. Next, it describes the process and methods for building an index system of evaluation and considers the compared evaluation and the logical framework approach, analytic hierarchy process (AHP), and the data envelopment analysis (DEA) relative efficiency evaluation method.Unique in its emphasis on the practical applications of systems evaluation methods and models, the book introduces several new evaluation models of grey system, including general grey incidence model, grey incidence models based on similarity and closeness, grey cluster evaluation based on triangular whitenization functions, and multi-attribute grey target decision model. Explaining intricate concepts in language that is easy to understand it provides step-by-step explanations of the various methods and models.The text illustrates the practical application, analysis, and computation of systems evaluation methods and models with an abundance of practical examples and empirical studies. The case studies examine post evaluation of road-bridge construction projects, the efficiency evaluation of the science and technology activities, the evaluation of energy-saving projects in China, and the evaluation and selection of international cooperation projects.

Measurement Data Modeling and Parameter Estimation integrates mathematical theory with engineering practice in the field of measurement data processing. Presenting the first-hand insights and experiences of the authors and their research group, it summarizes cutting-edge research to facilitate the application of mathematical theory in measurement and control engineering, particularly for those interested in aeronautics, astronautics, instrumentation, and economics. Requiring a basic knowledge of linear algebra, computing, and probability and statistics, the book illustrates key lessons with tables, examples, and exercises. It emphasizes the mathematical processing methods of measurement data and avoids the derivation procedures of specific formulas to help readers grasp key points quickly and easily. Employing the theories and methods of parameter estimation as the fundamental analysis tool, this reference: Introduces the basic concepts of measurements and errorsApplies ideas from mathematical branches, such as numerical analysis and statistics, to the modeling and processing of measurement dataExamines methods of regression analysis that are closely related to the mathematical processing of dynamic measurement dataCovers Kalman filtering with colored noises and its applicationsConverting time series models into problems of parameter estimation, the authors discuss modeling methods for the true signals to be estimated as well as systematic errors. They provide comprehensive coverage that includes model establishment, parameter estimation, abnormal data detection, hypothesis tests, systematic errors, trajectory parameters, and modeling of radar measurement data. Although the book is based on the authors’ research and teaching experience in aeronautics and astronautics data processing, the theories and methods introduced are applicable to processing dynamic measurement data across a wide range of fields.

Tackling the question of how to effectively aggregate uncertain preference information in multiple structures given by decision-making groups, Theory and Approaches of Unascertained Group Decision-Making focuses on group aggregation methods based on uncertainty preference information. It expresses the complexity existing in each group decision-making process by employing complex networks and studying various methods of aggregating preference information from various unascertained, time-series based decision-making groups' structures. Written by Jianjun Zhu, director of the Chinese Society for Optimization, Overall Planning, and Economic Mathematics, the book starts by examining case studies of group decision making. It discusses consistency measuring and ranking methods of interval number reciprocal judgment matrix and interval number complementary judgment matrix. Next, it presents an unascertained number preference and a three-point interval number preference. Investigating linguistic preferences, the text provides two consistencies definitions. It considers the aggregating methods of several uncertain preferences as well as the multistage aggregating model of uncertain preference. The final chapter proposes an aggregating model of multistage linguistic information based on TOPSIS. The research in this book is supported by a number of scientific foundations from the People’s Republic of China, including the National Natural Science Foundation of China; the Social Science Foundation of China, Jiangsu Province; and the Soft Science Foundation of China.

Extension innovation method is an approach to originality generation. It utilizes basic theories of Extenics, a new discipline for modeling contradiction problems with formalized methods and transformation, to establish a modeling and quantification combined method that can be learned effortlessly and operated conveniently. This book introduces and analyzes commonly used extension innovation methods are introduced and analyzed thoroughly. It makes it easy for readers at different levels and of different knowledge backgrounds to study. Highly accessible cases faciliate understanding and application of the models.

As a powerful approach to data reasoning, rough set theory has proven to be invaluable in knowledge acquisition, decision analysis and forecasting, and knowledge discovery. With the ability to enhance the advantages of other soft technology theories, hybrid rough set theory is quickly emerging as a method of choice for decision making under uncertain conditions. Keeping the complicated mathematics to a minimum, Hybrid Rough Sets and Applications in Uncertain Decision-Making provides a systematic introduction to the methods and application of the hybridization for rough set theory with other related soft technology theories, including probability, grey systems, fuzzy sets, and artificial neural networks. It also: Addresses the variety of uncertainties that can arise in the practical application of knowledge representation systems Unveils a novel hybrid model of probability and rough setsIntroduces grey variable precision rough set models Analyzes the advantages and disadvantages of various practical applications The authors examine the scope of application of the rough set theory and discuss how the combination of variable precision rough sets and dominance relations can produce probabilistic preference rules out of preference attribute decision tables of preference actions. Complete with numerous cases that illustrate the specific application of hybrid methods, the text adopts the latest achievements in the theory, method, and application of rough sets.

Presenting the most recent statistical data, Investment and Employment Opportunities in China provides first-of-its-kind coverage of the regional economic, industrial, investment, and employment structures in China. After establishing the theoretical foundation, the rest of the book utilizes the model and the methodology presented by the authors to analyze the various investment and employment structures within China.Addressing the problem of strategic optimization of macroeconomic systems, the book illustrates the current state of investment and employment opportunities in more than 30 provinces, cities, and autonomous regions within China. It explores the current direction of relevant structural adjustments, orders, and intensities.The book employs the concept of comparative earnings and relevant models and addresses the problem of strategic optimization of a macroeconomic system, involving economic structures such as regions, industries, sectors, investments, employment, and distributions. A must-read for anyone considering investing in or seeking employment in China, it supplies proven theorems, methods, and concrete suggestions for navigating the various economic structures within China.Although the book provides suggestions on optimizing economic structures in China, the theories presented are general and can be used to investigate the investment and employment climate of other countries and regions. Outlining the basic conditions of imbalances in China’s regional economic and industrial structures, the guidelines presented in this volume will help you make more informed decisions regarding international investment and employment opportunities around the world.

Introduction to Theory of Control in Organizations explains how methodologies from systems analysis and control theory, including game and graph theory, can be applied to improve organizational management. The theory presented extends the traditional approach to management science by introducing the optimization and game-theoretical tools required to account for the special nature of human beings being viewed as control objects.The book introduces a version of mechanism design that has been customized to solve the problems that today’s managers must contend with. All mathematical models and mechanisms studied are motivated by the most common problems encountered by managers in firms and non-profit organizations.Requiring no prior knowledge of game theory or mechanism design, the book includes a systematic introduction to the underlying methodology of modern theory of control in organizations. The authors use formal methods to construct robust and efficient decision-making procedures which support all aspects and stages of management activity over all decision horizons—from operational to strategic management.The mathematical and methodological backgrounds of the organizational mechanisms discussed are not limited to game theory but also include systems analysis, control theory, operations research, and discrete mathematics.The book includes a set of exercises in each chapter—from simple to advanced—that provide the reader with the understanding required to integrate advanced methods of optimization, game theory, and mechanism design into daily managerial practice.

Along with the development of economic globalization, many countries have begun to relax their controls on their capital accounts. However, the recent financial crises in Latin American countries as well as the exchange rate crises in Southeast Asian countries have shown that there is major risk associated with capital account liberalization.This book details the benefits and risks of capital account liberalization and explains how to take an open-door policy at the appropriate time in order to reduce the risk to the lowest possible level. Supplying a complete mathematical analysis framework for the study of the problem of capital account liberalization, it presents a few important models that have been developed for the study of capital account liberalization.Next, the book examines the influence of capital account liberalization on the stability of financial markets by greatly expanding the scope of ordinary differential equation theory to the analysis of local stabilities. It conveys cutting-edge results while providing a general yet simple analysis framework, enriched with practical experiences from developing countries.This book applies the theory of limit cycles to the study of problems related to capital account liberalization and discusses the contagion of financial crises among different countries. Many problems related to capital account liberalization are formulated as optimization models, showing the fact that much broader economic issues can be solved by employing optimization methods.The book concludes by comparing the contagion effect of financial markets between nations with a relatively high degree of openness with those characterized by a moderate degree of openness. Explaining how to determine optimal capital inflows and outflows, this book provides you with the understanding required to accurately determine the characteristics, backgrounds, causes, and roles of capital account liberalization and relevant capital flows.

To make the best decisions, you need the best information. However, because most issues in game theory are grey, nearly all recent research has been carried out using a simplified method that considers grey systems as white ones. This often results in a forecasting function that is far from satisfactory when applied to many real situations. Grey Game Theory and Its Applications in Economic Decision Making introduces classic game theory into the realm of grey system theory with limited knowledge. The book resolves three theoretical issues: A game equilibrium of grey game A reasonable explanation for the equilibrium of a grey matrix of static nonmatrix game issues based on incomplete informationThe Centipede Game paradox, which has puzzled theory circles for a long time and greatly enriched and developed the core methods of subgame Nash perfect equilibrium analysis as a resultThe book establishes a grey matrix game model based on pure and mixed strategies. The author proposes the concepts of grey saddle points, grey mixed strategy solutions, and their corresponding structures and also puts forward the models and methods of risk measurement and evaluation of optimal grey strategies. He raises and solves the problems of grey matrix games. The book includes definitions of the test rules of information distortion experienced during calculation, the design of tokens based on new interval grey numbers, and new arithmetic laws to manipulate grey numbers. These features combine to provide a practical and efficient tool for forecasting real-life economic problems.

Based on research projects supported by the National Natural Science Foundation of China and Nanjing University of Aeronautics and Astronautics, Optimization of Regional Industrial Structures and Applications provides an authoritative introduction to and survey of the cutting-edge research and applications in industrial structure optimization. Employing grey systems theory as its method of analysis, it integrates grey systems theory with industrial structure optimization theory to provide dynamic and efficient methods of measurement, analysis, and decision making. The authors cover several models of grey regional industrial structure, including grey correlation priority analysis, industrial structure order degree measurement model, regional leading industries grey assessment model and turnpike model. The first part of the book clarifies basic theory. This section covers the production and development of industrial structure theory, evolution laws of industrial structure, rationalization and upgrading of industrial structures, factors of industrial structure upgrading, input–output analysis, and mathematical modeling of regional industrial structures. The second section introduces four case studies that illustrate real-world research and applications. It considers the approaches and measures taken in China’s industrial structure upgrade during the "eleventh five-year plan". The case studies examine measures of and strategies for Jiangsu province’s industrial structural adjustment.This section also presents the optimization and promotion study of the "eleventh five" industrial structure of another city in China. The models detailed in this book not only develop application fields of grey systems theory, but also enrich the theories of industrial structure optimization. All of the methods presented in the text are reviewed in the case studies to supply readers with a vivid and practical understanding.

As a powerful approach to data reasoning, rough set theory has proven to be invaluable in knowledge acquisition, decision analysis and forecasting, and knowledge discovery. With the ability to enhance the advantages of other soft technology theories, hybrid rough set theory is quickly emerging as a method of choice for decision making under uncertain conditions. Keeping the complicated mathematics to a minimum, Hybrid Rough Sets and Applications in Uncertain Decision-Making provides a systematic introduction to the methods and application of the hybridization for rough set theory with other related soft technology theories, including probability, grey systems, fuzzy sets, and artificial neural networks. It also: Addresses the variety of uncertainties that can arise in the practical application of knowledge representation systems Unveils a novel hybrid model of probability and rough setsIntroduces grey variable precision rough set models Analyzes the advantages and disadvantages of various practical applications The authors examine the scope of application of the rough set theory and discuss how the combination of variable precision rough sets and dominance relations can produce probabilistic preference rules out of preference attribute decision tables of preference actions. Complete with numerous cases that illustrate the specific application of hybrid methods, the text adopts the latest achievements in the theory, method, and application of rough sets.

A Novel Method to Analyze Problems and Encourage Systemic ThinkingReal-Life Case Studies Illustrate the Application of the Systemic Yoyo Model in Diverse AreasWritten by the co-creator of the systemic yoyo model, Systemic Yoyos: Some Impacts of the Second Dimension shows how the yoyo model and its methodology can be employed to study many unsettled or extremely difficult problems in modern science and technology.The first part of the book presents the theoretical foundation of the yoyo model and its empirical justifications. The author then shows how to use the model to address and resolve several problems in scientific areas, such as Newtonian physics, planetary motions, and the three-body problem, as well as economics and finance, such as Becker’s rotten kid theorem. The following part discusses the structure of human thoughts, infinity problems in the system of modern mathematics, and the fourth crisis of mathematics. The book concludes with a section on the concept of rolling currents, which can help predict weather changes, especially the arrival of disastrous weather conditions.Focusing on complex, unresolved issues in modern science, this book thoroughly explains the novel yoyo model and how it can be used to better understand wage differentials, weather patterns, and more.

A book in the Systems Evaluation, Prediction, and Decision-Making Series, Systems Evaluation: Methods, Models, and Applications covers the evolutionary course of systems evaluation methods, clearly and concisely. Outlining a wide range of methods and models, it begins by examining the method of qualitative assessment. Next, it describes the process and methods for building an index system of evaluation and considers the compared evaluation and the logical framework approach, analytic hierarchy process (AHP), and the data envelopment analysis (DEA) relative efficiency evaluation method.Unique in its emphasis on the practical applications of systems evaluation methods and models, the book introduces several new evaluation models of grey system, including general grey incidence model, grey incidence models based on similarity and closeness, grey cluster evaluation based on triangular whitenization functions, and multi-attribute grey target decision model. Explaining intricate concepts in language that is easy to understand it provides step-by-step explanations of the various methods and models.The text illustrates the practical application, analysis, and computation of systems evaluation methods and models with an abundance of practical examples and empirical studies. The case studies examine post evaluation of road-bridge construction projects, the efficiency evaluation of the science and technology activities, the evaluation of energy-saving projects in China, and the evaluation and selection of international cooperation projects.

Measurement Data Modeling and Parameter Estimation integrates mathematical theory with engineering practice in the field of measurement data processing. Presenting the first-hand insights and experiences of the authors and their research group, it summarizes cutting-edge research to facilitate the application of mathematical theory in measurement and control engineering, particularly for those interested in aeronautics, astronautics, instrumentation, and economics. Requiring a basic knowledge of linear algebra, computing, and probability and statistics, the book illustrates key lessons with tables, examples, and exercises. It emphasizes the mathematical processing methods of measurement data and avoids the derivation procedures of specific formulas to help readers grasp key points quickly and easily. Employing the theories and methods of parameter estimation as the fundamental analysis tool, this reference: Introduces the basic concepts of measurements and errorsApplies ideas from mathematical branches, such as numerical analysis and statistics, to the modeling and processing of measurement dataExamines methods of regression analysis that are closely related to the mathematical processing of dynamic measurement dataCovers Kalman filtering with colored noises and its applicationsConverting time series models into problems of parameter estimation, the authors discuss modeling methods for the true signals to be estimated as well as systematic errors. They provide comprehensive coverage that includes model establishment, parameter estimation, abnormal data detection, hypothesis tests, systematic errors, trajectory parameters, and modeling of radar measurement data. Although the book is based on the authors’ research and teaching experience in aeronautics and astronautics data processing, the theories and methods introduced are applicable to processing dynamic measurement data across a wide range of fields.

Along with the development of economic globalization, many countries have begun to relax their controls on their capital accounts. However, the recent financial crises in Latin American countries as well as the exchange rate crises in Southeast Asian countries have shown that there is major risk associated with capital account liberalization.This book details the benefits and risks of capital account liberalization and explains how to take an open-door policy at the appropriate time in order to reduce the risk to the lowest possible level. Supplying a complete mathematical analysis framework for the study of the problem of capital account liberalization, it presents a few important models that have been developed for the study of capital account liberalization.Next, the book examines the influence of capital account liberalization on the stability of financial markets by greatly expanding the scope of ordinary differential equation theory to the analysis of local stabilities. It conveys cutting-edge results while providing a general yet simple analysis framework, enriched with practical experiences from developing countries.This book applies the theory of limit cycles to the study of problems related to capital account liberalization and discusses the contagion of financial crises among different countries. Many problems related to capital account liberalization are formulated as optimization models, showing the fact that much broader economic issues can be solved by employing optimization methods.The book concludes by comparing the contagion effect of financial markets between nations with a relatively high degree of openness with those characterized by a moderate degree of openness. Explaining how to determine optimal capital inflows and outflows, this book provides you with the understanding required to accurately determine the characteristics, backgrounds, causes, and roles of capital account liberalization and relevant capital flows.

Introduction to Theory of Control in Organizations explains how methodologies from systems analysis and control theory, including game and graph theory, can be applied to improve organizational management. The theory presented extends the traditional approach to management science by introducing the optimization and game-theoretical tools required to account for the special nature of human beings being viewed as control objects.The book introduces a version of mechanism design that has been customized to solve the problems that today’s managers must contend with. All mathematical models and mechanisms studied are motivated by the most common problems encountered by managers in firms and non-profit organizations.Requiring no prior knowledge of game theory or mechanism design, the book includes a systematic introduction to the underlying methodology of modern theory of control in organizations. The authors use formal methods to construct robust and efficient decision-making procedures which support all aspects and stages of management activity over all decision horizons—from operational to strategic management.The mathematical and methodological backgrounds of the organizational mechanisms discussed are not limited to game theory but also include systems analysis, control theory, operations research, and discrete mathematics.The book includes a set of exercises in each chapter—from simple to advanced—that provide the reader with the understanding required to integrate advanced methods of optimization, game theory, and mechanism design into daily managerial practice.

Tackling the question of how to effectively aggregate uncertain preference information in multiple structures given by decision-making groups, Theory and Approaches of Unascertained Group Decision-Making focuses on group aggregation methods based on uncertainty preference information. It expresses the complexity existing in each group decision-making process by employing complex networks and studying various methods of aggregating preference information from various unascertained, time-series based decision-making groups' structures. Written by Jianjun Zhu, director of the Chinese Society for Optimization, Overall Planning, and Economic Mathematics, the book starts by examining case studies of group decision making. It discusses consistency measuring and ranking methods of interval number reciprocal judgment matrix and interval number complementary judgment matrix. Next, it presents an unascertained number preference and a three-point interval number preference. Investigating linguistic preferences, the text provides two consistencies definitions. It considers the aggregating methods of several uncertain preferences as well as the multistage aggregating model of uncertain preference. The final chapter proposes an aggregating model of multistage linguistic information based on TOPSIS. The research in this book is supported by a number of scientific foundations from the People’s Republic of China, including the National Natural Science Foundation of China; the Social Science Foundation of China, Jiangsu Province; and the Soft Science Foundation of China.