Genetic algorithms and classifier systems: foundations and future directions
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
The nature of statistical learning theory
The nature of statistical learning theory
Principle of information diffusion
Fuzzy Sets and Systems
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
What is evolutionary computation?
IEEE Spectrum
Intelligent Sensory Evaluation: Methodologies and Applications
Intelligent Sensory Evaluation: Methodologies and Applications
Neural Networks: A Comprehensive Foundation (3rd Edition)
Neural Networks: A Comprehensive Foundation (3rd Edition)
Self organization of a massive document collection
IEEE Transactions on Neural Networks
Extraction of rules from artificial neural networks for nonlinear regression
IEEE Transactions on Neural Networks
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This paper proposes a novel intelligent system for improving product formula design with sensory evaluation. The analyses and tests we carried out have shown that the proposed intelligent system is efficient for cigarette quality management, formula maintenance and new product design. Genetic algorithms, neural networks, support vector machines (SVMs) and fuzzy set method have been combined with expert knowledge in this system. The corresponding specialized knowledge can be extracted from trained neural nets or SVMs for mapping from tobacco cigarette chemical properties to sensory-quality indexes, classification of tobaccos, analysis of the correlation between chemical ingredients and sensory-quality indexes, and cigarette formula management and design.