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Springer Hybrid Intelligent Systems: Analysis and Design 208

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Description

Explore advanced methods for the analysis and design of hybrid intelligent systems in this technical volume from Springer. As part of the Studies in Fuzziness and Soft Computing series, this book focuses on the integration of soft computing (SC) techniques to address the complexity of real-world challenges. By combining various computing paradigms, such as fuzzy logic, neural networks, and genetic algorithms, researchers can develop powerful systems capable of handling high-dimensional data. This text provides the necessary framework for applying these combined techniques to critical fields including pattern recognition, time series prediction, and intelligent control. Whether you are working in robotics, automation, or complex data analysis, this book offers insights into building robust hybrid models. It serves as a specialized resource for understanding how multiple soft computing methods work together to solve problems that single-paradigm systems cannot manage alone.

Key Features

Covers essential soft computing paradigms including fuzzy logic, neural networks, and genetic algorithms for system design.

Provides methods for creating hybrid intelligent systems to manage high dimensionality and complex real-world problems.

Offers technical applications for pattern recognition and time series prediction tasks.

Supports development in advanced fields such as robotics, automation, and intelligent control systems.

Part of the professional Studies in Fuzziness and Soft Computing series by Springer.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
19 November 2010
Listed Since
01 October 2010

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No barcode data available

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