Title of article :
An expert system using rough sets theory for aided conceptual design of ship’s engine room automation
Author/Authors :
Shao، نويسنده , , Xin-Yu and Chu، نويسنده , , Xue-Zheng and Qiu، نويسنده , , Hao-Bo and Gao، نويسنده , , Liang and Yan، نويسنده , , Jun، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2009
Abstract :
More and more complicated conceptual design of ship’s engine room (CDSER) heavily depends on designers’ engineering knowledge and existing ship data. To achieve intelligent design at the initial ship design stage, many researchers have made much significant progress in this field, however, most of them only focused on how to find the similar constructed ships. At present, how to utilize these existing data remains an untouched topic. In order to make good use of the existing data and reduce the dependence on designers’ experience, a novel system named Expert System for Aided Conceptual Design of Ship’s Engine Room Automation (ESACD), is elaborated in this study. With the support of the constructed Ship Data Warehouse System, two core subsystems Configuration Selection Assistant (CSA) and Design Scheme Decision Assistant (DSDA) are included in ESACD. A promising approach integrating Fuzzy c-means algorithm (FCM) and Rough Sets Theory (RST) to extract configuration rules from the stored data is adopted in CSA. According to engineers’ proposals, RST is utilized to reason knowledge in incomplete scheme information systems for getting design scheme rules in DSDA, which are useful suggestions for engineers to get better schemes at this stage. Finally, the validity and necessity of this interactive expert system are demonstrated through the CDSER of a new 50,000 DWT Handymax bulk carrier. It is proved that ESACD can efficiently facilitate rapid and intelligent design in CDSER, and reduce the cost of a new ship design.
Keywords :
Rough sets theory (RST) , Conceptual design of ship’s engine room (CDSER) , discretization , Configuration of engine room , Design schemes
Journal title :
Expert Systems with Applications
Journal title :
Expert Systems with Applications