Study Of Ship Resistance Prediction Model Based On BP Neural Network And Demonstration Model Of The Main Dimensions

One of the key technologies of Hull form design is the hydrodynamic performance of its forecast.And its resistance prediction is the important aspects.It is designed for low resistance hull form and good decision engine power, propulsion, and other design basis.Therefore, the research for a reliable and accurate method of ship resistance estimate gets great significance.Ship resistance prediction methods are as following: test method, computational fluid dynamics simulation method and some approximate estimation methods.When the main factor is decided,we estimate for the ship resistance and make comparative analysis of the pros and cons of various programmes.For this stage Ship Line has not yet been determined,we can not determine resistance by ship model test and CFD simulation method is lack of high precision and reliability.Based on the test result data and maps, neural network prediction model is a strong, with high precision and reliability,method of resistance forecast.In this paper,first of all,we makes a review about the estimate of ship resistance and the development of neural network.So the research has clearly established research programmes.And MATLAB software tools used were outlined.Then,we focuse on the application of neural network,combined with test data and maps, construct neural network model forecast the ship resistance,and get many useful conclusions.And also we collect the current methods of ship resistance prediction, and the programs of selection model of the main dimensions are achieved.Finally, the practical application for the project is proposed.