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Fuzzy Logic is an analytical tool used in the modeling of those phenomena that fall outside the scope of exact sciences. It is used in the analysis of complex and highly nonlinear processes, where mathematical models or standard classic logic cannot define conditions inherent to such processes, e.g. human thinking. Kurt Peray's detailed analysis of the new approaches and techniques for Risk Control and Portfolio Asset Allocation - which uses the principles of Fuzzy Logic - helps you to make decisions as to when to buy, hold or sell. While making independent and educated decisions, you will be able to hedge your portfolio from the volatile forces in the market, and will offset the erosive impact of inflation and taxation. In this electronic age, investors have quick access to important information relevant to the decision process. The guidelines and formulas that serve as foundations to the Fuzzy Logic approach gives you the ability to build customized programs. Investing in Mutual Funds Using Fuzzy Logic is for the individual who wants to invest in financial instruments that will provide a return for growth. With the investment approach he devised, Peray guides the you towards achieving your investment goals.
In the world of mathematics, the study of fuzzy relations and its theories are well-documented and a staple in the area of calculative methods. What many researchers and scientists overlook is how fuzzy theory can be applied to industries outside of arithmetic. The framework of fuzzy logic is much broader than professionals realize. There is a lack of research on the full potential this theoretical model can reach. The Handbook of Research on Emerging Applications of Fuzzy Algebraic Structures provides emerging research exploring the theoretical and practical aspects of fuzzy set theory and its real-life applications within the fields of engineering and science. Featuring coverage on a broad range of topics such as complex systems, topological spaces, and linear transformations, this book is ideally designed for academicians, professionals, and students seeking current research on innovations in fuzzy logic in algebra and other matrices.
The International Conference on Information Processing and Management of - certainty in Knowledge-Based Systems, IPMU, is organized every two years with the aim of bringing together scientists working on methods for the management of uncertainty and aggregation of information in intelligent systems. Since 1986, this conference has been providing a forum for the exchange of ideas between th theoreticians and practitioners working in these areas and related ?elds. The 13 IPMU conference took place in Dortmund, Germany, June 28–July 2, 2010. This volume contains 79 papers selected through a rigorous reviewing process. The contributions re?ect the richness of research on topics within the scope of the conference and represent several important developments, speci?cally focused on theoretical foundations and methods for information processing and management of uncertainty in knowledge-based systems. We were delighted that Melanie Mitchell (Portland State University, USA), Nihkil R. Pal (Indian Statistical Institute), Bernhard Sch ̈ olkopf (Max Planck I- titute for Biological Cybernetics, Tubing ̈ en, Germany) and Wolfgang Wahlster (German Research Center for Arti?cial Intelligence, Saarbruc ̈ ken) accepted our invitations to present keynote lectures. Jim Bezdek received the Kamp ́ede F ́ eriet Award, granted every two years on the occasion of the IPMU conference, in view of his eminent research contributions to the handling of uncertainty in clustering, data analysis and pattern recognition.
This revised, enlarged and up to date edition of a very successful book is the most important of its kind regarding the mutual funds industry in India. It provides a thorough analysis of mutual funds to the general public and fund managers alike.
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.
"This book is a collection of research on the advancement of intelligent technology in industrial environments and its applications within the manufacturing field"--
Artificial intelligence (AI) describes machines/computers that mimic cognitive functions that humans associate with other human minds, such as learning and problem solving. As businesses have evolved to include more automation of processes, it has become more vital to understand AI and its various applications. Additionally, it is important for workers in the marketing industry to understand how to coincide with and utilize these techniques to enhance and make their work more efficient. The Handbook of Research on Applied AI for International Business and Marketing Applications is a critical scholarly publication that provides comprehensive research on artificial intelligence applications within the context of international business. Highlighting a wide range of topics such as diversification, risk management, and artificial intelligence, this book is ideal for marketers, business professionals, academicians, practitioners, researchers, and students.
Experts from the world's major financial institutions contributed to this work and have already used the newest technologies. Gives proven strategies for using neural networks, algorithms, fuzzy logic and nonlinear data analysis techniques to enhance profitability. The latest analytical breakthroughs, the impact on modern finance theory and practice, including the best ways for profitably applying them to any trading and portfolio management system, are all covered.
The purpose of this paper was to model, with the help of neutrosophic fuzzy numbers, the optimal financial asset portfolios, offering additional information to those investing in the capital market. The optimal neutrosophic portfolios are those categories of portfolios consisting of two or more financial assets, modeled using neutrosophic triangular numbers, that allow for the determination of financial performance indicators, respectively the neutrosophic average, the neutrosophic risk, for each financial asset, and the neutrosophic covariance as well as the determination of the portfolio return, respectively of the portfolio risk.