Combined Bayesian Networks and Rough-Granular Approaches for Discovery of Process Models Based on Vehicular Traffic Simulation

被引：0
|
作者：
Adamczyk, Mateusz [1 ]
Betlinski, Pawel [1 ]
Gora, Pawel [1 ]
机构：
[1] Warsaw Univ, Inst Informat, PL-02097 Warsaw, Poland
来源：
INFORMATION PROCESSING AND MANAGEMENT OF UNCERTAINTY IN KNOWLEDGE-BASED SYSTEMS: THEORY AND METHODS, PT 1 | 2010年 / 80卷
关键词：
Granules; ontology; domain knowledge; ontology approximation; hierarchical classifier; rough sets; Bayesian network; time window; process mining; cellular automaton; traffic modelling;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The aim of this paper is to summarize our experiments for discovering process of creation of traffic jams. These experiments were conducted during work on our master theses. We obtained data sets from the vehicular traffic simulator which were used to create a proper ontology based on the domain knowledge. The ontology was used as a schema for hierarchical classifier, which used Bayesian network created by genetic algorithm and rough sets based methods.
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页码：278 / 287
页数：10
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