A new architecture of object-oriented rule base management system

2003 ◽  
Author(s):  
Chang-Jiun Tsai ◽  
Shian-Shyong Tseng ◽  
Yu-Co Wu
Keyword(s):  
Management System ◽  
Object Oriented ◽  
Rule Base ◽  
Base Management System ◽  
Base Management

The model, language, and implementation of an object-oriented multimedia knowledge base management system

1993 ◽  
Vol 18 (1) ◽  
pp. 1-50 ◽  
Author(s):  
Hiroshi Ishikawa ◽  
Fumio Suzuki ◽  
Fumihiko Kozakura ◽  
Akifumi Makinouchi ◽  
Mika Miyagishima ◽  
...  
Keyword(s):  
Knowledge Base ◽  
Management System ◽  
Object Oriented ◽  
Base Management System ◽  
Base Management ◽  
Knowledge Base Management

Research on Management System of Automatic Driver Decision-Making Knowledge Base for Unmanned Vehicle

2019 ◽  
Vol 33 (04) ◽  
pp. 1959013 ◽  
Author(s):  
Zhaoxia Zhang ◽  
Qing Jiang ◽  
Rujing Wang ◽  
Liangtu Song ◽  
Zhengyong Zhang ◽  
...  
Keyword(s):  
Decision Making ◽  
Knowledge Base ◽  
Management System ◽  
Autonomous Driving ◽  
Unmanned Vehicles ◽  
Knowledge Model ◽  
Unmanned Vehicle ◽  
Base Management System ◽  
Decision Making System ◽  
Base Management

The acquisition, presentation and management of autonomous driving decision-making knowledge of unmanned vehicles are the key and difficult issues in the autonomous driving decision-making system of unmanned vehicles. This paper presents a knowledge model, which includes problem description layer and problem-solving knowledge layer. The automatic driving decision knowledge base of unmanned vehicle is composed of a set of knowledge models. Knowledge model supports knowledge representation and reasoning. Based on the WEB visualization knowledge modeling tool and visualization knowledge service tool, we construct the decision-making knowledge base management system for autonomous driving of unmanned vehicles and then construct the autonomous driving decision-making system of unmanned vehicles. The reasoning example shows that the knowledge base management system can effectively improve the knowledge acquisition, representation and maintenance efficiency of autonomous driving decision-making system, which is of great significance in enhancing the intelligence level of autonomous driving decision-making system.

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