Fuzzy knowledge and fuzzy systems affect our lives today as systems enter the world of commerce. Fuzzy systems are incorporated in domestic appliances (washing machine, air conditioning, microwave, telephone) and in transport systems (a pilotless helicopter has recently completed a test flight). Future applications are expected to have dramatic implications for the demand for labor, among other things. It was with such thoughts in mind that this first international survey of future applications of fuzzy logic has been undertaken. The results are likely to be predictive for a decade beyond the millenium. The predictive element is combined with a bibliography which serves as an historical anchor as well as being both extensive and extremely useful. Analysis and Evaluation of Fuzzy Systems is thus a milestone in the development of fuzzy logic and applications of three representative subsystems: Fuzzy Control, Fuzzy Pattern Recognition and Fuzzy Communications.

“Ecosystem Assessment and Fuzzy Systems Management” is the edited outcome of the 3rd International Conference on Ecosystem Assessment Management (ICEAM) and the Workshop on the Construction of an Early Warning Platform for Eco-tourism (WCEWPE) in Hainan on May 5-12, 2013, Haikou, China. The 3rd ICEAM and the WCEWPE, built on the success of previous conferences, are major Symposiums for scientists, engineers and logistic management researchers presenting their the latest achievements, developments and applications in all areas of Ecosystem Assessment Management, Early Warning Platform for Eco-tourism and fuzziology. It aims to strengthen relations between industry research laboratories and universities, and to create a primary symposium for world scientists. The book, containing 47 papers, is divided into five parts: “Ecosystem Assessment, Management and Information”; “Intelligent Algorithm, Fuzzy Optimization and Engineering Application”; “Spatial Data Analysis and Intelligent Information Processing”; “Tourism Culture, Development and Planning” and “Application of Operations Research and Fuzzy Systems”.

In today’s increasingly complex and uncertain business environment, financial analysis is yet more critical to business managers who tackle problems of an economic or business nature. Knowledge based on formal logic and even experience becomes less sufficient. This volume systematically sets out the basic elements on which to base financial analysis for business in the new century. It incorporates a previous work that can serve as the basis and foundation for the new contributions that are now being made in the field of financial economy and intend to provide business with instruments and models suitable for dealing with the new economic context. In dealing with rapid and unpredictable changes in technological and business conditions, it postulates a growing reliance on the opinions of experts instead of past data or probabilistic forecasts, which is a radical change but may yield fruitful results. For this reason, much emphasis is devoted to the problem of aggregation of the opinion of experts in the financial field, with the object of limiting, wherever possible, the subjective component of the opinions and making sure that the decisions have the best guarantee of reaching the desired objectives.

The intensity of global competition and ever-increasing economic uncertainties has led organizations to search for more efficient and effective ways to manage their business operations. Data envelopment analysis (DEA) has been widely used as a conceptually simple yet powerful tool for evaluating organizational productivity and performance. Fuzzy DEA (FDEA) is a promising extension of the conventional DEA proposed for dealing with imprecise and ambiguous data in performance measurement problems. This book is the first volume in the literature to present the state-of-the-art developments and applications of FDEA. It is designed for students, educators, researchers, consultants and practicing managers in business, industry, and government with a basic understanding of the DEA and fuzzy logic concepts.

The interdisciplinary field of fuzzy logic encompass applications in the electrical, industrial, chemical and engineering realms as well as in areas of management and environmental issues, while data mining covers new approaches to big data, massive data, and scalable, parallel and distributed algorithms. This book presents papers from the 6th International Conference on Fuzzy Systems and Data Mining (FSDM 2020). The conference was originally due to be held from 13-16 November 2020 in Xiamen, China, but was changed to an online conference held on the same dates due to ongoing restrictions connected with the COVID-19 pandemic. The annual FSDM conference provides a platform for knowledge exchange between international experts, researchers academics and delegates from industry. This year, the committee received 316 submissions, of which 76 papers were selected for inclusion in the conference; an acceptance rate of 24%. The conference covers four main areas: fuzzy theory; algorithms and systems, which includes topics like stability; foundations and control; and fuzzy applications, which are widely used and cover various types of processing as well as hardware and architecture for big data and time series. Providing a current overview of research and developments in fuzzy logic and data mining, the book will be of interest to all those working in the field of data science.

Fuzzy systems and data mining are indispensible aspects of the computer systems and algorithms on which the world has come to depend. This book presents papers from FSDM 2021, the 7th International Conference on Fuzzy Systems and Data Mining. The conference, originally due to take place in Seoul, South Korea, was held online on 26-29 October 2021, due to ongoing restrictions connected with the COVID-19 pandemic. The annual FSDM conference provides a platform for knowledge exchange between international experts, researchers, academics and delegates from industry. This year, the committee received 266 submissions, and this book contains 52 papers, including keynotes and invited presentations, oral and poster contributions. The papers cover four main areas: 1) fuzzy theory, algorithms and systems – including topics like stability; 2) fuzzy applications – which are widely used and cover various types of processing as well as hardware and architecture for big data and time series; 3) the interdisciplinary field of fuzzy logic and data mining; and 4) data mining itself. The topic most frequently addressed this year is fuzzy systems. The book offers an overview of research and developments in fuzzy logic and data mining, and will be of interest to all those working in the field of data science.

In recent years, substantial efforts are being made in the development of reliability theory including fuzzy reliability theories and their applications to various real-life problems. Fuzzy set theory is widely used in decision making and multi criteria such as management and engineering, as well as other important domains in order to evaluate the uncertainty of real-life systems. Fuzzy reliability has proven to have effective tools and techniques based on real set theory for proposed models within various engineering fields, and current research focuses on these applications. Advancements in Fuzzy Reliability Theory introduces the concept of reliability fuzzy set theory including various methods, techniques, and algorithms. The chapters present the latest findings and research in fuzzy reliability theory applications in engineering areas. While examining the implementation of fuzzy reliability theory among various industries such as mining, construction, automobile, engineering, and more, this book is ideal for engineers, practitioners, researchers, academicians, and students interested in fuzzy reliability theory applications in engineering areas.

This book constitutes the refereed proceedings of the Third International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2006, held in federation with the Second International Conference on Natural Computation ICNC 2006. The book presents 115 revised full papers and 50 revised short papers. Coverage includes neural computation, quantum computation, evolutionary computation, DNA computation, fuzzy computation, granular computation, artificial life, innovative applications to knowledge discovery, finance, operations research, and more.

Fuzzy Systems Modeling in Environmental and Health Risk Assessment Demonstrates the successful application of fuzzy systems modeling to real-world environmental and health problems In Fuzzy Systems Modeling in Environmental and Health Risk Assessment, a team of distinguished researchers delivers an up-to-date collection of the most successful and innovative attempts to apply fuzzy logic to problems involving environmental risk assessment, healthcare decision-making, the management of water distribution networks, and the optimization of water treatment and waste management systems. By explaining both the theoretical and practical aspects of using fuzzy systems modeling methods to solve complex problems, analyze risks and optimize system performance, this handy guide maintains a strongly application-oriented perspective throughout, offering readers a practical treatment of a cutting-edge subject. Readers will also find: Comprehensive explorations of the practical applications of fuzzy systems modeling in environmental science Practical advice on environmental quality assessments and human health risk analyses In-depth case studies involving air and water pollution, solid waste, indoor swimming pool and landfill risk assessments, wastewater treatment, and more Perfect for environmental engineers and scientists, Fuzzy Systems Modeling in Environmental and Health Risk Assessment will also benefit policy makers, computer scientists, mathematicians, and researchers and practitioners interested in applying soft computing theories to environmental problems.