This paper is devoted to the issue of forecasting financial ratios. The objective of the conducted research is to develop a predictive model with the use of an innovative methodology, i.e., fuzzy logic theory, and to evaluate its effectiveness. Fuzzy logic has been widely used in machinery, robotics and industrial engineering. This paper introduces the use of fuzzy logic for the financial analysis of enterprises. While many current phenomena in finance and economics are fuzzy, they are treated as if they are crisp. Fuzzy logic provides an appropriate tool for modeling imprecise, uncertain and ambiguous phenomena. Because the financial situation of a company is affected by many factors (economic, political, psychological, etc.) that cannot be precisely and unambiguously defined, the approach used in this paper greatly enhances the predictive power of financial analysis and makes it an economically useful tool for the management of enterprises. Empirically, this paper employs three testing samples: Central European enterprises, Latin American companies and global firms. From the verification of these models, it is evident that the refined processes are effective in improving the forecasting of financial situations of all three types of enterprises. The models created by the author are characterized by high efficiency. This study is one of the world's first attempts to combine ratio analysis with fuzzy logic to predict the financial situations of companies.

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 success of any activity and process depends fundamentally on the possibility of balancing (symmetry) needs and their satisfaction. That is, the ability to properly define a set of success indicators. The application of the developed new multi-criteria decision-making (MCDM) methods can be eliminated or decreased by decision-makers’ subjectivity, which leads to consistency or symmetry in the weight values of the criteria. In this Special Issue, 40 research papers and one review study co-authored by 137 researchers from 23 different countries explore aspects of multi-criteria modeling and optimization in crisp or uncertain environments. The papers propose new approaches and elaborate case studies in the following areas of application: MCDM optimization in sustainable engineering, environmental sustainability in engineering processes, sustainable multi-criteria production and logistics processes planning, integrated approaches for modeling processes in engineering, new trends in the multi-criteria evaluation of sustainable processes, and multi-criteria decision-making in strategic management based on sustainable criteria.

This monograph is designed to introduce methods of dealing with uncertainty so often present in problems of accounting. Traditionally, uncertainty in accounting was handled by statistical methods, but this book applies fuzzy logic, the theory of evidence and rough sets to the problem.

Financial rates, in terms of investors, are of great importance in the expansion of the companies to whose share they are going to invest. Financial rates have been benefited from especially in determining the risk while a portfolio is being formed, in changing the existing risk or in determining the alternative shares. In literature has been researched whether more than average income of the market is possible to obtain considering financial rates.In this respect, using fuzzy logic method the companies that are the subjects in the study are clustered and it is presented to the investors as a risk scale. The investor, according to the portfolio he/she is going to form, can not only determine which shares he/she should buy but he/she will be able to learn about the share which has the same profit level and the same risk as well if the share he/she wants to buy is not available.What is aimed to be achieved in this study is helping the investor form a portfolio and the companies at question be clustered with the help of financial rates.

In this hands-on, practical guide, you'll walk through powerful fuzzy logic business applications for business, including risk assessment, forecasting, supplier evaluation, customer targeting, and scheduling. You'll watch fuzzy logic at work analyzing credit risk, evaluating leases, making stock market decisions, and uncovering fraud.

This edited book presents the state-of-the-art of applying fuzzy logic to managerial decision-making processes in areas such as fuzzy-based portfolio management, recommender systems, performance assessment and risk analysis, among others. Presenting the latest research, with a strong focus on applications and case studies, it is a valuable resource for researchers, practitioners, project leaders and managers wanting to apply or improve their fuzzy-based skills.