Fuzzy Sets and Systems - Special issue: fuzzy sets: where do we stand? Where do we go?
Rough set methods and applications: new developments in knowledge discovery in information systems
Rough set methods and applications: new developments in knowledge discovery in information systems
Swarm intelligence
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Quantum computation and quantum information
Quantum computation and quantum information
Rough-Fuzzy Hybridization: A New Trend in Decision Making
Rough-Fuzzy Hybridization: A New Trend in Decision Making
Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing
Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
Rough-Fuzzy MLP: Modular Evolution, Rule Generation, and Evaluation
IEEE Transactions on Knowledge and Data Engineering
Molecular Computing
Case Generation Using Rough Sets with Fuzzy Representation
IEEE Transactions on Knowledge and Data Engineering
Natural computation and non-Turing models of computation
Theoretical Computer Science - Super-recursive algorithms and hypercomputation
Granular neural networks for land use classification
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Fundamentals of Natural Computing (Chapman & Hall/Crc Computer and Information Sciences)
Fundamentals of Natural Computing (Chapman & Hall/Crc Computer and Information Sciences)
Computing is a natural science
Communications of the ACM - Creating a science of games
The many facets of natural computing
Communications of the ACM
Handbook of Granular Computing
Handbook of Granular Computing
A novel approach to neuro-fuzzy classification
Neural Networks
Generalized rough sets, entropy, and image ambiguity measures
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on human computing
MGRS: A multi-granulation rough set
Information Sciences: an International Journal
Natural Computing: DNA, Quantum Bits, and the Future of Smart Machines
Natural Computing: DNA, Quantum Bits, and the Future of Smart Machines
Rough Fuzzy Image Analysis: Foundations and Methodologies
Rough Fuzzy Image Analysis: Foundations and Methodologies
Fuzzy rough granular neural networks, fuzzy granules, and classification
Theoretical Computer Science
Class-dependent rough-fuzzy granular space, dispersion index and classification
Pattern Recognition
Rough Set Based Generalized Fuzzy -Means Algorithm and Quantitative Indices
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fuzzy logic = computing with words
IEEE Transactions on Fuzzy Systems
Granular Neural Networks With Evolutionary Interval Learning
IEEE Transactions on Fuzzy Systems
Rough fuzzy MLP: knowledge encoding and classification
IEEE Transactions on Neural Networks
Multilayer perceptron, fuzzy sets, and classification
IEEE Transactions on Neural Networks
Rough-Fuzzy Pattern Recognition: Applications in Bioinformatics and Medical Imaging
Rough-Fuzzy Pattern Recognition: Applications in Bioinformatics and Medical Imaging
| Hi-index | 0.00 |
Natural computing, inspired by biological course of action, is an interdisciplinary field that formalizes processes observed in living organisms to design computational methods for solving complex problems, or designing artificial systems with more natural behaviour. Based on the tasks abstracted from natural phenomena, such as brain modelling, self-organization, self-repetition, self evaluation, Darwinian survival, granulation and perception, nature serves as a source of inspiration for the development of computational tools or systems that are used for solving complex problems. Nature inspired main computing paradigms used for such development include artificial neural networks, fuzzy logic, rough sets, evolutionary algorithms, fractal geometry, DNA computing, artificial life and granular or perception-based computing. Information granulation in granular computing is an inherent characteristic of human thinking and reasoning process performed in everyday life. The present article provides an overview of the significance of natural computing with respect to the granulation-based information processing models, such as neural networks, fuzzy sets and rough sets, and their hybridization. We emphasize on the biological motivation, design principles, application areas, open research problems and challenging issues of these models.