In this paper, the index of fuzziness and fuzzy entropy were applied to image segmentation, the new definition of fuzzy maximum entropy was proposed and the concept of exponential entropy was imported.
More particularly, Genetic Algorithms, Artificial Neural Networks and Fuzzy Logic methods seem to be the most promising tools to speed up and optimize the search for new leads and focused libraries.
This paper deals with a secretary problem on fuzzy sets, which allows both the recall of applicants and the uncertainty of a current applicant receiving an offer of employment.
A kind of fuzzy linear programming problems based on interval-valued fuzzy sets
The objective of this paper is to deal with a kind of fuzzy linear programming problem based on interval-valued fuzzy sets (IVFLP) through the medium of procedure that turns IVFLP into parametric linear programming via the mathematical programming.
Approximation capabilities of multilayer feedforward regular fuzzy neural networks
Boolean parallel algorithm is improved to discover frequent fuzzy attribute set, and the fuzzy association rules with at least a minimum confidence are generated on all processors.
The example shows that the accuracy of classification systems of the fuzzy association rules is better than that of the two popular classification methods: C4.5 and CBA.
The experimental results show that the method not only can correctly detect the fuzzy edge and exiguous edge but can evidently improve the searching efficiency of fuzzy clustering algorithm based on IEA.
The fuzzy control inputs were based on the front barrier distance and the difference between the left and right barrier distance measured by ultrasonic sensors; the output was the direction angle.
Based on the analysis of the control objects' dynamic characteristics, historical control information (substituting for the deviation change rate) is used as the basis for decision-making of the fuzzy control.
Basic behavior effects of these models, sources and forms of data fuzziness in the computing process, means for controlling this event, and confidence limits in the simulating process are studied.
Problems in data fusion systems are complex by nature and can often be characterized by not only randomness but also fuzziness.
Stochastic geometry is a valuable tool for fighting fuzziness inherent in some applied problems of pattern recognition.
It is shown that by taking the fuzziness into consideration, the fuzzy pattern recognition and optimization method reflects more efficiently the fuzzy nature of the groundwater vulnerability to pollution and is more applicable in reality.
Due to the subjectivity and fuzziness of pulse diagnosis, quantitative methods are needed.