Based on α-cut sets representation of fuzzy set ,this paper has proposed an easily quantifiable approach to generalize Bayesian networks under fuzzy a prior and fuzzy sample data. The combination of bayesian statisti...Based on α-cut sets representation of fuzzy set ,this paper has proposed an easily quantifiable approach to generalize Bayesian networks under fuzzy a prior and fuzzy sample data. The combination of bayesian statistics and fuzzy set theory will improve advanced fuzzy control to include stochastic information processing and higher level control knowledge representation. Also the approach can facilitate more natural and wider scope knowledge representation in Bayesian networks in general.展开更多
This paper presents a new method of comparing or ranking of interval and fuzzy numbers. Based on another way of understanding fuzzy concept, the paper proposes the concept of number meaning of interval and the compari...This paper presents a new method of comparing or ranking of interval and fuzzy numbers. Based on another way of understanding fuzzy concept, the paper proposes the concept of number meaning of interval and the comparison method of interval. The paper defines the new ranking method by the α cut intervals of fuzzy number, and proves that the new inequality relation of fuzzy numbers is transitive. Our approach is a simple way of considering all the existence levels and can be calculated at different exact level according to different applications.展开更多
文摘Based on α-cut sets representation of fuzzy set ,this paper has proposed an easily quantifiable approach to generalize Bayesian networks under fuzzy a prior and fuzzy sample data. The combination of bayesian statistics and fuzzy set theory will improve advanced fuzzy control to include stochastic information processing and higher level control knowledge representation. Also the approach can facilitate more natural and wider scope knowledge representation in Bayesian networks in general.
文摘This paper presents a new method of comparing or ranking of interval and fuzzy numbers. Based on another way of understanding fuzzy concept, the paper proposes the concept of number meaning of interval and the comparison method of interval. The paper defines the new ranking method by the α cut intervals of fuzzy number, and proves that the new inequality relation of fuzzy numbers is transitive. Our approach is a simple way of considering all the existence levels and can be calculated at different exact level according to different applications.
