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Hierarchical Modular Granular Neural Networks with Fuzzy Aggregation

) approach, thus resulting in a new concept of MNNs; modular granular neural networks (MGNNs). In addition fuzzy logic (FL) and hierarchical;

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New Hybrid Intelligent Systems for Diagnosis and Risk Evaluation of Arterial Hypertension

as a hybrid intelligent system combining modular neural net-works and fuzzy systems. The different responses of the hybrid system are;

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Hierarchical Type-2 Fuzzy Aggregation of Fuzzy Controllers

This book focuses on the fields of fuzzy logic, granular computing and also considering the control area. These areas can work together;

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Fuzzy Neural Intelligent Systems

networks, offers a better way of combining fuzzy logic systems with neural networks, and explores some of their engineering applications. Dividing;

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Computational Intelligence

the aspects of fuzzy, neural and evolutionary approaches with worked out examples, MATLAB(R) exercises and applications in each chapter;

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Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms

. The chapters start with the design of a new fuzzy-neural controller. Remaining chapters discuss the application of expert systems, neural;

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Understanding Neural Networks And Fuzzy Logic

Understand the fundamentals of the emerging field of fuzzy neural networks, their applications and the most used paradigms with this;

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Deep Neuro-Fuzzy Systems with Python

relations, and fuzzy inference Review neural networks, back propagation, and optimization Work with different architectures such as Takagi-Sugeno;

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Evolutionary Machine Learning Techniques

neural networks, self-optimizing neural networks, radial basis function networks, recurrent neural networks, spiking neural networks, neuro-fuzzy;

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Evolutionary Machine Learning Techniques

neural networks, self-optimizing neural networks, radial basis function networks, recurrent neural networks, spiking neural networks, neuro-fuzzy;

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Fuzzy Logic and Neural Networks

In this title, fuzzy logic and neural networks have been discussed in detail through illustrative examples, methods and generic;

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Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision Tools

The research presented in this book shows how combining deep neural networks with a special class of fuzzy logical rules and multi-criteria;

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Type 2 Fuzzy Neural Networks and Their Applications

This book deals with the theory, design principles, and application of hybrid intelligent systems using type-2 fuzzy sets in combination;

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Blind Equalization in Neural Networks

The book begins with an introduction of blind equalization theory and its application in neural networks, then discusses the algorithms;

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Secure Clustering in Multi-Modal Wireless Sensor Networks

Hierarchical clustering (SecHC) and Virtual ECC Group Key (VEGK) as SecHC update. In addition, we believe that merging the security with clustering;

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Fuzzy and Multi-Level Decision Making

-computing-based techniques, including fuzzy sets, neural networks, genetic algorithms and particle swarm optimization, and shows how these;

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Handbook of Granular Computing

. The Handbook of Granular Computing offers a comprehensive reference source for the granular computing community, edited by and with;

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Knowledge-Based Neurocomputing

integrates the merits of symbolic fuzzy rule-bases and sub-symbolic artificial neural networks, and yields a new approach for knowledge-based;

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New Classification Method Based on Modular Neural Networks with the LVQ Algorith

In this book a new model for data classification was developed. This new model is based on the competitive neural network Learning Vector;

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Neural Networks & Fuzzy-Logic Control On Personal Computers & Workstations + D3

algorithms with pulldown menus. This hands-on tutorial demonstrates both neural networks and fuzzy-logic control with a different approach. A natural;

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Hybrid Intelligent Systems in Control, Pattern Recognition and Medicine

This book describes the latest advances in fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations;

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Hybrid Intelligent Systems in Control, Pattern Recognition and Medicine

This book describes the latest advances in fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations;

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Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms

We describe in this book, recent developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid;

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Supervised and Unsupervised Pattern Recognition

research begins with an introduction to Neural Networks, classifiers, and feature extraction methods. It then addresses unsupervised and fuzzy;

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Information Processing and Management of Uncertainty

set; intelligent databases and information systems; theory of evidence; aggregation functions; big data - the role of fuzzy methods; imprecise;

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Neural Networks and Fuzzy Logic

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Artificial Intelligence and Expert Systems

engineering, expert systems, neural networks, and fuzzy logic, etc. The book has been structured into five parts with an emphasis on expert systems;

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