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This paper presents a novel method to odor based identification of alcoholic beverages using steady-state responses of a thick film tin oxide sensor array exposed to four different types of whiskies. A neural classifier designed to perform the identification task was trained by incorporating the class information in the training data set in the form of fuzzy entropies of the respective classes. The...
Development of expert system for indoor artificial ice skating rink can make the cumbersome manual design calculation and drawing process simply, and can shorten the construction period and improve work efficiency. Intelligent engineering design software was completed by using the computer programming, combined with neural networks and fuzzy calculation methods. The software is able to realize optimal...
A hybrid intelligent fault diagnosis method is presented for the diversity, uncertainty and complexity of device faults. This method integrates respective advantages of fault tree, fuzzy theory, neural networks and genetic algorithms to form a hybrid approach and is applied to fault diagnosis of fan. Experiments show that this method is simple and effective. It can also be applied to other fault diagnosis...
This paper describes a comprehensive method to construct fuzzy classification system considering both precision and interpretability. Fuzzy classification system, initialized by modified Gath-Geva fuzzy clustering algorithm, is transformed into neural network. After training the neural network, fuzzy sets similarity measure is adopt to merge redundant fuzzy sets to improve interpretability, and a...
The detection of explosives in passengers?? luggage is an important area in public traffic security. This paper presents a united classification system for detecting explosives based on fuzzy rule and neural networks. Due to imaging and influence of outer environment, preprocessing is firstly needed to improve the quality of X-ray images. Then, a test pattern may be considered as several possible...
Based on introduction of the background and the limitations of present prediction methods for gas outburst in coal mines, this paper focuses on introducing a new decision-making approach to coal and gas outburst prediction with multi-sensor information fusion. Two of the multi-sensor information fusion methods, neural network and the Dempster-Shafter evidence theory, were taken into account, and the...
Rough set theory offers a novel approach to manage uncertainty that has been used for the discovery of data dependencies, importance of features, patterns in sample data, feature space dimensionality reduction, and the classification of objects. Consequently, rough sets have been successfully employed for various image processing tasks including image segmentation, enhancement and classification....
In this paper, an automated fault diagnosis system essentially based on neural networks and fuzzy logic, in a hybrid scheme, is suggested. First, a signal classification and image classification, resulting in a signal diagnosis and image diagnosis respectively, are developed. Such dual-classification is then exploited in a fuzzy system 1 to ensure a satisfactory reliability to medical diagnosis and...
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