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This book presents the first algebraic treatment of quasi-truth fuzzy logic and covers the algebraic foundations of many-valued logic.  It offers a comprehensive account of basic techniques and reports on important results showing the pivotal role played by perfect many-valued algebras (MV-algebras). It is well known that the first-order predicate Łukasiewicz logic is not complete with respect to the canonical set of truth values.  However, it is complete with respect to all linearly ordered MV –algebras.  As there are no simple linearly ordered MV-algebras in this case, infinitesimal elements of an MV-algebra are allowed to be truth values. The book presents perfect algebras as an interesting subclass of local MV-algebras and provides readers with the necessary knowledge and tools for formalizing the fuzzy concept of quasi true and quasi false. All basic concepts are introduced in detail to promote a better understanding of the more complex ones. It is an advanced and inspiring reference-guide for graduate students and researchers in the field of non-classical many-valued logics.

Computer Science --- Engineering & Applied Sciences --- Engineering. --- Computer science --- Algebra. --- Computational intelligence. --- Computational Intelligence. --- General Algebraic Systems. --- Symbolic and Algebraic Manipulation. --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Mathematics --- Mathematical analysis --- Computer mathematics --- Discrete mathematics --- Electronic data processing --- Construction --- Industrial arts --- Technology --- Mathematics. --- Algebra --- Data processing. --- Computer science—Mathematics. --- Fuzzy logic.

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This book provides a thorough introduction to the challenge of applying mathematics in real-world scenarios. Modelling tasks rarely involve well-defined categories, and they often require multidisciplinary input from mathematics, physics, computer sciences, or engineering. In keeping with this spirit of modelling, the book includes a wealth of cross-references between the chapters and frequently points to the real-world context. The book combines classical approaches to modelling with novel areas such as soft computing methods, inverse problems, and model uncertainty. Attention is also paid to the interaction between models, data and the use of mathematical software. The reader will find a broad selection of theoretical tools for practicing industrial mathematics, including the analysis of continuum models, probabilistic and discrete phenomena, and asymptotic and sensitivity analysis. .

Mathematics. --- Computer simulation. --- Computer mathematics. --- Mathematical models. --- Applied mathematics. --- Engineering mathematics. --- Mathematical Modeling and Industrial Mathematics. --- Appl.Mathematics/Computational Methods of Engineering. --- Computational Science and Engineering. --- Simulation and Modeling. --- Engineering --- Engineering analysis --- Models, Mathematical --- Computer mathematics --- Discrete mathematics --- Electronic data processing --- Computer modeling --- Computer models --- Modeling, Computer --- Models, Computer --- Simulation, Computer --- Math --- Mathematics --- Computer science. --- Mathematical and Computational Engineering. --- Informatics --- Science --- Mathematical analysis --- Electromechanical analogies --- Mathematical models --- Simulation methods --- Model-integrated computing --- Maths for engineers. --- Maths for scientists.