Learning automata: an introduction
Learning automata: an introduction
Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy information engineering: a guided tour of applications
Fuzzy information engineering: a guided tour of applications
The ordered weighted averaging operators: theory and applications
The ordered weighted averaging operators: theory and applications
OWA operators for doctoral student selection problem
The ordered weighted averaging operators
Applications of the linguistic OWA operators in group decision making
The ordered weighted averaging operators
Using OWA operator in flexible query processing
The ordered weighted averaging operators
Application of OWA operators to soften information retrieval systems
The ordered weighted averaging operators
OWA-based computing: learning algorithms
The ordered weighted averaging operators
Selection of relevant features and examples in machine learning
Artificial Intelligence - Special issue on relevance
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
Information-theoretic algorithm for feature selection
Pattern Recognition Letters
Dimensionality Reduction in Unsupervised Learning of Conditional Gaussian Networks
IEEE Transactions on Pattern Analysis and Machine Intelligence
Intelligent Hybrid Systems: Fuzzy Logic, Neural Networks, and Genetic Algorithms
Intelligent Hybrid Systems: Fuzzy Logic, Neural Networks, and Genetic Algorithms
Learning Algorithms Theory and Applications
Learning Algorithms Theory and Applications
Aggregation and Fusion of Imperfect Information
Aggregation and Fusion of Imperfect Information
Machine Learning
Efficient Feature Selection in Conceptual Clustering
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Active learning with statistical models
Journal of Artificial Intelligence Research
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Reinforcement structure/parameter learning for neural-network-based fuzzy logic control systems
IEEE Transactions on Fuzzy Systems
Using mutual information for selecting features in supervised neural net learning
IEEE Transactions on Neural Networks
Kansei evaluation based on prioritized multi-attribute fuzzy target-oriented decision analysis
Information Sciences: an International Journal
Journal of Intelligent Manufacturing
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Sensory evaluation has been widely applied in different industrial fields especially for quality inspection, product design and marketing. Classically, factorial multivariate methods are the only tool for analyzing and modeling sensory data provided by experts, panelists or consumers. These methods are efficient for solving some problems but sometimes cause important information lost. In this situation, new methods based on intelligent techniques such as fuzzy logic, neural networks, data aggregation, classification, clustering have been applied for solving uncertainty and imprecision related to sensory evaluation. These new methods can be used together with the classical ones in a complementary way for obtaining relevant information from sensory data. This paper outlines the general background of sensory evaluation and the corresponding industrial interests and explicitly indicates some orientations for further development by IT researchers.