欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
针对医院信息系统中积累的大量数据，探讨了采用粗糙集、规则推理、贝叶斯网络相结合的方法基于这类数据进行学习建模．该方法在粗糙集属性约简的基础上，考虑了规则推理的影响，对信息表中的属性列进行压缩，获取最少属性列．基于最少属性的贝叶斯网络模型可以有效降低网络结构的复杂性;同时利用贝叶斯网络实现概率推理．最后进行了实验分析，结果证明该方法快速有效．
英文摘要：
This paper discusses the modeling using the combination of rough sets, rule based reasoning and Bayesian network （BN） based on the large amounts of data in hospital information system. On the basis of attributes reduction algorithm of rough set, the proposed method takes synthetically into account the influences of rule-based reasoning. The limitation of attribute variable in information tables was compressed. The minimal attributes was obtained via the compression of attribute columns. Due to the acquisition of minimal attributes, the complexity of BN structure was largely decreased; probability reasoning could be realized by BN. The efficiency of this method is validated by the practical examples.
同期刊论文项目
同项目期刊论文
An argument-dependent approach to determining OWA operator weights based on the rule of maximum entr
Consumer preference prediction by using a hybrid evidential reasoning and belief rule-based methodol
Applying a belief rule-base inference methodology to a guideline-based clinical decision support sys
Integrating classification capability and reliability in associative classification: A beta-stronger
Analyzing the applicability of Dempster’s rule to the combination of interval-valued belief structur
ASSESSMENT OF STRATEGIC R&D PROJECTS FOR CAR MANUFACTURERS BASED ON THE EVIDENTIAL REASONING APPROAC
期刊信息
位置：