Aiming at the problem that it is difficult to model user requirements with fuzzy characteristics in existing ship conceptual scheme design (SCSD), this study focuses on a rapid SCSD system based on a fuzzy inference system (FIS) that can quickly obtain ship performance values that meet the user requirements and generate the corresponding ship hull design parameter values.

First, the existing ship hull parameter data is collected and sorted as prior knowledge for hyper-parameter initialization in the process of user requirement modeling. Second, based on the fuzzy set theory, the user requirements are quantitatively mapped to the fuzzy space, and the sorted prior knowledge is used to infer the ship performance values that meet the user requirements in an interpretable way. Finally, the best ship hull design parameters are matched for each ship performance value that meets the user requirements, and through the "AND" principle in fuzzy set theory, the ship design parameters that meet all the user requirements for ship performance are further inferred and taken as the SCSD.

The experimental results show that the intelligent FIS can quickly infer multiple SCSDs with deviations within 3.5% according to the fuzzy user requirements within 30 seconds.

The intelligent FIS quantifies the fuzziness in user requirements, and after two stages of inference, the SCSD that meets the various user requirements is efficiently generated. The results of this study can provide useful references for rapid intelligent SCSD generation.