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Fuzzy Decision Analysis: Multi Attribute Decision Making Approach
Authored by a leading expert in the field, this book introduces an innovative methodology that harnesses the power of fuzzy logic to enhance decision-making in multi-attribute scenarios. In a world of complexity and uncertainty, effective decision-making is paramount. Springer proudly presents a cutting-edge publication that revolutionizes decision analysis: "Fuzzy Decision Analysis: Multi-attribute Decision-Making Approach." This book stands at the forefront of decision analysis, introducing the integration of fuzzy logic into multi-attribute decision-making. It is a transformative journey into the realm of advanced decision analysis. It book not only equips you with the knowledge to comprehend the theoretical underpinnings but also empowers you to apply these insights in practical scenarios. This book serves as your indispensable companion. Its comprehensive coverage serves as a beacon, guiding you through the intricate maze of fuzzy logic and multi-attribute decision-making, ultimately empowering you to embrace innovation and master the art of making well-informed decisions in an ever-changing world.
Data Envelopment Analysis with R
This book introduces readers to the use of R codes for optimization problems. First, it provides the necessary background to understand data envelopment analysis (DEA), with a special emphasis on fuzzy DEA. It then describes DEA models, including fuzzy DEA models, and shows how to use them to solve optimization problems with R. Further, it discusses the main advantages of R in optimization problems, and provides R codes based on real-world data sets throughout. Offering a comprehensive review of DEA and fuzzy DEA models and the corresponding R codes, this practice-oriented reference guide is intended for masters and Ph.D. students in various disciplines, as well as practitioners and researchers.
A Hybrid BSC-DEA Model with Indeterminate Information
Strategy is the main source of long-term growth for organizations, and if it is not successfully implemented, even if appropriate ones are adopted, the process is futile. The balanced scorecard which focuses on four aspects such as growth and learning, internal processes, customer, and financial is considered as a comprehensive framework for assessing performance and the progress of the strategy. Moreover, the data envelopment analysis is one of the best mathematical methods to compute the efficiency of organizations. The combination of these two techniques is a significant quantitative measurement with respect to the organization’s performance. However, in the real world, determinate and indeterminate information exists. Henceforth, the indeterminate issues are inescapable and must be considered in the performance evaluation. Neutrosophic number is a helpful tool for dealing with information that is indeterminate and incomplete.
Fuzzy Fractional Differential Operators and Equations
This book contains new and useful materials concerning fuzzy fractional differential and integral operators and their relationship. As the title of the book suggests, the fuzzy subject matter is one of the most important tools discussed. Therefore, it begins by providing a brief but important and new description of fuzzy sets and the computational calculus they require. Fuzzy fractals and fractional operators have a broad range of applications in the engineering, medical and economic sciences. Although these operators have been addressed briefly in previous papers, this book represents the first comprehensive collection of all relevant explanations. Most of the real problems in the biological and engineering sciences involve dynamic models, which are defined by fuzzy fractional operators in the form of fuzzy fractional initial value problems. Another important goal of this book is to solve these systems and analyze their solutions both theoretically and numerically. Given the content covered, the book will benefit all researchers and students in the mathematical and computer sciences, but also the engineering sciences.
An Introduction to Computing with Fuzzy Sets
This book provides concise yet thorough coverage of the fundamentals and technology of fuzzy sets. Readers will find a lucid and systematic introduction to the essential concepts of fuzzy set-based information granules, their processing and detailed algorithms. Timely topics and recent advances in fuzzy modeling and its principles, neurocomputing, fuzzy set estimation, granulation–degranulation, and fuzzy sets of higher type and order are discussed. In turn, a wealth of examples, case studies, problems and motivating arguments, spread throughout the text and linked with various areas of artificial intelligence, will help readers acquire a solid working knowledge. Given the book’s well-balanced combination of the theory and applied facets of fuzzy sets, it will appeal to a broad readership in both academe and industry. It is also ideally suited as a textbook for graduate and undergraduate students in science, engineering, and operations research.
The Willingness to Pay for Education in Developing Countries
In recent years, citing the low price elasticity of demand for schooling, some economists have advocated increasing school fees to raise revenue for educational improvements in developing countries. But elasticities alone are not enough - one must estimate the willingness to pay for schooling improvements to see whether higher fees are in fact desirable. Using a rigorous theoretical model of the demand for schooling and the principle of compensating variations, the authors calculate the willingness to pay for new secondary schools in rural Peru. They find that rural Peruvian households are indeed willing to pay fees high enough to more than cover the operating costs of opening new secondary schools in their villages. This is even true of the poorest quarter of the income distribution.
Fuzzy Linear Programming: Solution Techniques and Applications
This book presents the necessary and essential backgrounds of fuzzy set theory and linear programming, particularly a broad range of common Fuzzy Linear Programming (FLP) models and related, convenient solution techniques. These models and methods belong to three common classes of fuzzy linear programming, namely: (i) FLP problems in which all coefficients are fuzzy numbers, (ii) FLP problems in which the right-hand-side vectors and the decision variables are fuzzy numbers, and (iii) FLP problems in which the cost coefficients, the right-hand-side vectors and the decision variables are fuzzy numbers. The book essentially generalizes the well-known solution algorithms used in linear programmi...
Fuzzy Modelling
Provides recent information on fuzzy models, identification algorithms, and applications. Section I on relational models includes theory and case studies in areas such as speech recognition, prediction, and ecological systems. Section II on fuzzy neural networks covers fundamentals such as neurocomputing, explains the relationship between fuzzy systems and neural networks, and details architectures. Section III addresses design principles governing the development of rule-based models. Of interest to researchers and practitioners developing models of complex systems. Annotation copyright by Book News, Inc., Portland, OR
Nonlinear Analysis
Contents: Fixed Point Theory and Nonlinear Problems (Th Rassias)Global Linearization Iterative Methods and Nonlinear Partial Differential Equations III (M Altman)On Generalized Power Series and Generalized Operational Calculus and Its Application (M Al-Bassam)Multiple Solutions to Parametrized Nonlinear Differential Systems from Nielsen Fixed Point Theory (R Brown)The topology of Ind-Affine Sets (P Cherenack)Almost Approximately Polynomial Functions (P Cholewa)Cohomology Classes and Foliated Manifolds (M Craioveanu & M Puta)Bifurcation and Nonlinear Instability in Applied Mathematics (L Debnath)The Stability of Weakly Additive Functional (H Drljevic)Index Theory for G-Bundle Pairs with Appli...
Artificial Intelligence and Soft Computing
The two-volume set LNCS 12415 and 12416 constitutes the refereed proceedings of of the 19th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2020, held in Zakopane, Poland*, in October 2020. The 112 revised full papers presented were carefully reviewed and selected from 265 submissions. The papers included in the first volume are organized in the following six parts: neural networks and their applications; fuzzy systems and their applications; evolutionary algorithms and their applications; pattern classification; bioinformatics, biometrics and medical applications; artificial intelligence in modeling and simulation. The papers included in the second volume are organized in the following four parts: computer vision, image and speech analysis; data mining; various problems of artificial intelligence; agent systems, robotics and control. *The conference was held virtually due to the COVID-19 pandemic.
