This exceptional guide and reference is devised for practitioners who want to employ fuzzy logic concepts in the design and deployment of actual fuzzy systems. FUZZY SYSTEMS DESIGN PRINCIPLES concentrates on the IF-THEN fuzzy algorithm, one of the most popular algorithms implemented today. The "basic fuzzy inference algorithm," the IF-THEN structure is not only applicable to many types of problems, but is also comprised of building blocks used in the development of other types of fuzzy systems used in today's electronic and software products. Sponsored by: IEEE Neural Networks Council.

Since their inception, fuzzy sets and fuzzy logic became popular. The reason is that the very idea of fuzzy sets and fuzzy logic attacks an old tradition in science, namely bivalent (black-or-white, all-or-none) judg ment and reasoning and the thus resulting approach to formation of scientific theories and models of reality. The idea of fuzzy logic, briefly speaking, is just the opposite of this tradition: instead of full truth and falsity, our judgment and reasoning also involve intermediate truth values. Application of this idea to various fields has become known under the term fuzzy approach (or graded truth approach). Both prac tice (many successful engineering applications) and theory (interesting nontrivial contributions and broad interest of mathematicians, logicians, and engineers) have proven the usefulness of fuzzy approach. One of the most successful areas of fuzzy methods is the application of fuzzy relational modeling. Fuzzy relations represent formal means for modeling of rather nontrivial phenomena (reasoning, decision, control, knowledge extraction, systems analysis and design, etc. ) in the pres ence of a particular kind of indeterminacy called vagueness. Models and methods based on fuzzy relations are often described by logical formulas (or by natural language statements that can be translated into logical formulas). Therefore, in order to approach these models and methods in an appropriate formal way, it is desirable to have a general theory of fuzzy relational systems with basic connections to (formal) language which enables us to describe relationships in these systems.

In recent years, a great number of publications have explored the use of genetic algorithms as a tool for designing fuzzy systems. Genetic Fuzzy Systems explores and discusses this symbiosis of evolutionary computation and fuzzy logic. The book summarizes and analyzes the novel field of genetic fuzzy systems, paying special attention to genetic algorithms that adapt and learn the knowledge base of a fuzzy-rule-based system. It introduces the general concepts, foundations and design principles of genetic fuzzy systems and covers the topic of genetic tuning of fuzzy systems. It also introduces the three fundamental approaches to genetic learning processes in fuzzy systems: the Michigan, Pittsburgh and Iterative-learning methods. Finally, it explores hybrid genetic fuzzy systems such as genetic fuzzy clustering or genetic neuro-fuzzy systems and describes a number of applications from different areas.Genetic Fuzzy System represents a comprehensive treatise on the design of the fuzzy-rule-based systems using genetic algorithms, both from a theoretical and a practical perspective. It is a valuable compendium for scientists and engineers concerned with research and applications in the domain of fuzzy systems and genetic algorithms.

Examines the methodology and algorithms of fuzzy sets considered mainly in the context of control engineering and system modelling and analysis. Special emphasis is focused on the processing of fuzzy information realized with the aid of fuzzy relational structures and their extensions.

“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”.

There are a myriad of mathematical problems that cannot be solved using traditional methods. The development of fuzzy expert systems has provided new opportunities for problem-solving amidst uncertainties. Fuzzy Systems: Concepts, Methodologies, Tools, and Applications is a comprehensive reference source on the latest scholarly research and developments in fuzzy rule-based methods and examines both theoretical foundations and real-world utilization of these logic sets. Featuring a range of extensive coverage across innovative topics, such as fuzzy logic, rule-based systems, and fuzzy analysis, this is an essential publication for scientists, doctors, engineers, physicians, and researchers interested in emerging perspectives and uses of fuzzy systems in various sectors.

Introduction to Fuzzy Systems provides students with a self-contained introduction that requires no preliminary knowledge of fuzzy mathematics and fuzzy control systems theory. Simplified and readily accessible, it encourages both classroom and self-directed learners to build a solid foundation in fuzzy systems. After introducing the subjec