Fuzzy Models In Economics
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Fuzzy Models in Economics
This book offers a timely guide to fuzzy methods applied to the analysis of socioeconomic systems. It provides readers with a comprehensive and up-to-date overview of the algorithms, including the theory behind them, as well as practical considerations, current limitations and solutions. Each chapter focuses on a different economic problem, explaining step by step the process to approach it, using the corresponding fuzzy tools. The book covers elements of intuitionistic fuzzy logics, fuzzy entropy and the fuzzy DEMATEL method, a fuzzy approach to calculate the financial stability index. It also reports on some new models of social, financial and ecological security, and on a novel fuzzy method for evaluating the quality of development of information economy.
Fuzzy Engineering Economics with Applications
Fuzzy set approaches are suitable to use when the modeling of human knowledge is necessary and when human evaluations are needed. Fuzzy set theory is recognized as an important problem modeling and solution technique. It has been studied ext- sively over the past 40 years. Most of the early interest in fuzzy set theory pertained to representing uncertainty in human cognitive processes. Fuzzy set theory is now - plied to problems in engineering, business, medical and related health sciences, and the natural sciences. This book handles the fuzzy cases of classical engineering e- nomics topics. It contains 15 original research and application chapters including different topics of fuzzy engineering economics. When no probabilities are available for states of nature, decisions are given under uncertainty. Fuzzy sets are a good tool for the operation research analyst facing unc- tainty and subjectivity. The main purpose of the first chapter is to present the role and importance of fuzzy sets in the economic decision making problem with the literature review of the most recent advances.
Fuzzy Mathematics in Economics and Engineering
The book aims at surveying results in the application of fuzzy sets and fuzzy logic to economics and engineering. New results include fuzzy non-linear regression, fully fuzzified linear programming, fuzzy multi-period control, fuzzy network analysis, each using an evolutionary algorithm; fuzzy queuing decision analysis using possibility theory; fuzzy differential equations; fuzzy difference equations; fuzzy partial differential equations; fuzzy eigenvalues based on an evolutionary algorithm; fuzzy hierarchical analysis using an evolutionary algorithm; fuzzy integral equations. Other important topics covered are fuzzy input-output analysis; fuzzy mathematics of finance; fuzzy PERT (project evaluation and review technique). No previous knowledge of fuzzy sets is needed. The mathematical background is assumed to be elementary calculus.