Isbn: 9786209749650 - intuitionistic fuzzy ann using linear space techniques & python (9 resultados)

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PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Taschenbuch. Condición: Neu. INTUITIONISTIC FUZZY ANN USING LINEAR SPACE TECHNIQUES & PYTHON | John Robinson P (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786209749650 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.…

Paperback. Condición: new. Paperback. Intuitionistic Fuzzy ANN Using Linear Space Techniques & Python presents a unified framework that integrates intuitionistic fuzzy set (IFS) theory with artificial neural networks (ANN) using linear space methodologies and computational tools in Python. The book addresses decision-making and learning problems involving uncertainty, hesitation, and incomplete information by embedding IFS-based representations, membership, non-membership, and hesitation into neural learning models. It systematically develops the mathematical foundations of IFS, linear algebraic learning structures, and ANN paradigms including perceptron, delta rule, and backpropagation. The proposed approach interprets learning geometrically through vector space concepts such as norms, projections, and transformations. The book also explores aggregation operators for MAGDM, hybrid fuzzy-neural architectures, and defuzzification-based learning strategies. Python implementations, algorithms, and case studies demonstrate applicability across engineering, environmental, healthcare, and policy decision systems, ensuring accuracy, stability, and reproducibility. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 160 pp. Englisch.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Intuitionistic Fuzzy ANN Using Linear Space Techniques & Python presents a unified framework that integrates intuitionistic fuzzy set (IFS) theory with artificial neural networks (ANN) using linear space methodologies and computational tools in Python. The book addresses decision-making and learning problems involving uncertainty, hesitation, and incomplete information by embedding IFS-based representations, membership, non-membership, and hesitation into neural learning models. It systematically develops the mathematical foundations of IFS, linear algebraic learning structures, and ANN paradigms including perceptron, delta rule, and backpropagation. The proposed approach interprets learning geometrically through vector space concepts such as norms, projections, and transformations. The book also explores aggregation operators for MAGDM, hybrid fuzzy-neural architectures, and defuzzification-based learning strategies. Python implementations, algorithms, and case studies demonstrate applicability across engineering, environmental, healthcare, and policy decision systems, ensuring accuracy, stability, and reproducibility.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 160 pp. Englisch.…

Paperback. Condición: new. Paperback. Intuitionistic Fuzzy ANN Using Linear Space Techniques & Python presents a unified framework that integrates intuitionistic fuzzy set (IFS) theory with artificial neural networks (ANN) using linear space methodologies and computational tools in Python. The book addresses decision-making and learning problems involving uncertainty, hesitation, and incomplete information by embedding IFS-based representations, membership, non-membership, and hesitation into neural learning models. It systematically develops the mathematical foundations of IFS, linear algebraic learning structures, and ANN paradigms including perceptron, delta rule, and backpropagation. The proposed approach interprets learning geometrically through vector space concepts such as norms, projections, and transformations. The book also explores aggregation operators for MAGDM, hybrid fuzzy-neural architectures, and defuzzification-based learning strategies. Python implementations, algorithms, and case studies demonstrate applicability across engineering, environmental, healthcare, and policy decision systems, ensuring accuracy, stability, and reproducibility. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Intuitionistic Fuzzy ANN Using Linear Space Techniques & Python presents a unified framework that integrates intuitionistic fuzzy set (IFS) theory with artificial neural networks (ANN) using linear space methodologies and computational tools in Python. The book addresses decision-making and learning problems involving uncertainty, hesitation, and incomplete information by embedding IFS-based representations, membership, non-membership, and hesitation into neural learning models. It systematically develops the mathematical foundations of IFS, linear algebraic learning structures, and ANN paradigms including perceptron, delta rule, and backpropagation. The proposed approach interprets learning geometrically through vector space concepts such as norms, projections, and transformations. The book also explores aggregation operators for MAGDM, hybrid fuzzy-neural architectures, and defuzzification-based learning strategies. Python implementations, algorithms, and case studies demonstrate applicability across engineering, environmental, healthcare, and policy decision systems, ensuring accuracy, stability, and reproducibility.…