Intuitionistic Fuzzy Ann Using Linear Space Techniques & Python - Softcover

Robinson P, John; A, Saranraj; S A, Arun Raja

Softcover

ISBN 10: 6209749658 ISBN 13: 9786209749650

Publisher: LAP Lambert Academic Publishing, 2026

Synopsis

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.

Edition details

• Publisher: LAP Lambert Academic Publishing
• Publication date: 2026
• Language: English
• ISBN 10: 6209749658
• ISBN 13: 9786209749650
• Binding: Paperback
• Number of pages: 160