Fuzzy logic and applications

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This comprehensive work explores various advancements in fuzzy set theory and its applications across multiple domains. It delves into foundational concepts like non-contradiction and excluded middle principles, and introduces definitions for approximate parallelism between fuzzy objects. The text discusses barycentric algebras in gene expression, fuzzy quantification, and the least squares method for L-R fuzzy variables. It also covers modeling interpretive steps in fuzzy logic computations and examines coherence in fuzzy answer set semantics for residuated logic programs. The book presents a rough set approach to rule induction from imprecise decision tables and introduces uninorm-based fuzzy networks for tree data structures. It surveys intuitionistic fuzzy sets, addressing conditional expectations and probabilities on IF-sets. Topics such as fuzzy classification, clustering, and a comparative study of rough ensemble classifiers are discussed, along with innovative techniques for cloud detection and fuzzy image processing. Advanced applications include a neuro-fuzzy approach for reconstructing concrete fissures, adaptive image watermarking, and a fuzzy inference expert system for military decision-making. The text also explores intelligent navigation systems and the reverse engineering of regulatory relations in gene networks, highlighting the versatility and impact of fuzzy logic in real-world scenarios.