摘要
事物的不确定现象包括模糊性和随机性.云模型通过对二者的结合,建立起定性定量的互换模型.相似云及其度量算法的提出使得云模型具有一定的理论价值和实际意义.然而由于云本身的特性,使得算法的计算精度不高、计算消耗较大.因此提出基于区间的云相似度比较算法,对原云相似性算法进行改进.实验证明,该算法在计算精度以及计算消耗上都有较大的优化.
Uncertainty phenomenon includes fuzziness and randomness.Cloud model built an exchange model between quantities and qualities by integrating fuzziness and randomness.The present of both similar cloud and its measurement algorithm made cloud model had some theory value and real meanings.However,the characteristic of cloud made the algorithm with low precision and high consumption of calculation.Based on these,interval-based cloud similar comparability algorithm was brought forward in this paper,which improved original cloud similarity algorithm.The experimental results show that this algorithm optimizes the precision and consumption of calculation.
出处
《小型微型计算机系统》
CSCD
北大核心
2011年第12期2456-2460,共5页
Journal of Chinese Computer Systems
基金
国家自然科学基金项目(61073182
61077063
60803036
60703090
61073183)资助
中央高校基本科研业务费专项资金项目(HEUCF1007
HEUCF100607)资助
哈尔滨工程大学青年骨干教师支持项目资助
关键词
云模型
相似云
云相似性算法
区间
比较
cloud model
similar cloud
cloud similarity algorithm
interval
compare
