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June 17, 2025, 12:55 p.m.
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SOURCE: Pedrycz W. Fuzzy Systems Engineering Toward Human-Centric Computing 2007
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COVER
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MEDIAINFO
Textbook in PDF format Over 40 years have already passed since the inception of fuzzy sets. During this period, we have witnessed a truly impressive wealth of theoretical developments and conceptual pursuits, emergence of novel methodologies, algorithmic environments, and a variety of applications. Contemporary technologies in the areas such as information storage and retrieval, web search, image processing and understanding, control, pattern recognition, bioinformatics and computational biology, e-markets, autonomous navigation, and guidance have benefited considerably from the developments in fuzzy sets. What becomes equally important is that we have accumulated a body of knowledge, developed sound design practices, and gained a comprehensive insight into the role of the technology of fuzzy sets in system design and analysis. With the existing affluence and apparent diversity of the landscape of intelligent systems, fuzzy sets exhibit an important and unique position by forming a unified framework supporting various facets of human-centric computing. Given the current trends in the information technology, it becomes apparent that the increasing level of intelligence, autonomy, and required flexibility comes hand in hand with the increased human centricity of resulting systems. This manifests at the end level when the delivered systems are expected to exhibit flexibility, significant communication abilities, user awareness, and a substantial level of adaptive behavior. The human-centric facet of processing (or human centricity, briefly) supported by the use of fuzzy sets is concerned with (a) user-friendly nature of the resulting systems (manifesting though a high level of context awareness, realization of relevance feedback, etc.), (b) forming a sound trade-off between accuracy and transparency (interpretability), and (c) incorporation of designer-friendly mechanisms of system development facilitating an efficient aggregation of various sources of available information being present at several quite different levels of abstraction (say, a highly seamless integration of domain knowledge and numeric experimental data). Introduction Notions and Concepts of Fuzzy Sets Characterization of Fuzzy Sets The Design of Fuzzy Sets Operations and Aggregations of Fuzzy Sets Fuzzy Relations Transformations of Fuzzy Sets Generalizations and Extensions of Fuzzy Sets Interoperability Aspects of Fuzzy Sets Fuzzy Modeling: Principles and Methodology Rule-Based Fuzzy Models From Logic Expressions to Fuzzy Logic Networks Fuzzy Systems and Computational Intelligence Granular Models and Human-Centric Computing Emerging Trends in Fuzzy Systems
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