摘要
本文建立应用反向传播学习算法的多层前馈神经网络模型，对运输船舶金属船体重量进行神经估算。以散货船和油船为实例的计算结果表明，由非线性模拟神经元组成的神经网络在船体重量估算中是非常有效的。
This paper deals with the neural estimation of the weight of metallic hull for transport ships based on the multilayer feed forward neural network model trained by using the backpropagation learning algorithm. It is shown by the computational results for bulk carriers and tankers that massively parallel, interconnected networks of nonlinear analog neurons are most effective in the hull weight estimation.
出处
《中国造船》
EI
CSCD
北大核心
1997年第3期93-99,共7页
Shipbuilding of China
