Application of RBF neural networks to resistance prediction of deep-V planning craft

The RBF neural network was applied to predicting the resistances of deep-V planning craft based on the measured data of resistance,wetted surface area,and trim of series SV and JYK.According to the limited tested data,a new resistance modified method was presented,which can be used to predict the resistance of planning craft with a range of dead rise angles.The experiment verifies the method of predicting the resistance of deep-V planning crafts,with the ratio of projected chine length to the maximum breadth over the chine 4~5.5,the area coefficient 5.5~7,the longitudinal location of the center of gravity 3%~9%,the stern dead rise angle 5°~25°.In the same precision,the time used by RBF network is less than that used by BP network in solving the problem.