Applied Decision Support With Soft Computing
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Applied Decision Support with Soft Computing
Author: Xinghuo Yu
language: en
Publisher: Springer Science & Business Media
Release Date: 2003-05-19
Soft computing has provided sophisticated methodologies for the development of intelligent decision support systems. Fast advances in soft computing technologies, such as fuzzy logic and systems, artificial neural networks and evolutionary computation, have made available powerful problem representation and modelling paradigms, and learning and optimisation mechanisms for addressing modern decision making issues. This book provides a comprehensive coverage of up-to-date conceptual frameworks in broadly perceived decision support systems and successful applications. Different from other existing books, this volume predominately focuses on applied decision support with soft computing. Areas covered include planning, management finance and administration in both the private and public sectors.
Applied Decision Support with Soft Computing
Soft computing has provided sophisticated methodologies for the development of intelligent decision support systems. Fast advances in soft computing technologies, such as fuzzy logic and systems, artificial neural networks and evolutionary computation, have made available powerful problem representation and modelling paradigms, and learning and optimisation mechanisms for addressing modern decision making issues. This book provides a comprehensive coverage of up-to-date conceptual frameworks in broadly perceived decision support systems and successful applications. Different from other existing books, this volume predominately focuses on applied decision support with soft computing. Areas covered include planning, management finance and administration in both the private and public sectors.
Fuzzy Hypersoft Expert Set with Application in Decision Making for the Best Selection of Product
Numerous researchers have made a few models dependent on soft set, to tackle issues in decision making and clinical analysis, yet a large portion of these models manage one expert. This causes an issue with the clients, particularly with the individuals who use polls in their work and studies.