Abstract:When it is difficult or even impossible to construct a precise model for solving a problem, the artificial neural networks (ANN) will show its advantage. The selection of the structure of ANN to deal with a specific problem is important. In this paper, six kinds of multilayer feedforward neural networks models were used for imaging spectral data pattern recognition of characteristic minerals, and their learning difficulties, operation efficiencies and recognition effects were studied synthetically.
收稿日期: 2004-03-08
出版日期: 2011-08-02
作者简介: 何勇强(1969-),男,讲师,主要研究方向为遥感图像处理技术、计算机软件开发.
引用本文:
何勇强, 姚国清. 用于成像光谱数据特征矿物识别的人工神经网络结构研究[J]. 国土资源遥感, 2004, 16(3): 23-27.
HE Yong-qiang, YAO Guo-qing . THE STRUCTURES OF ARTIFICIAL NEURAL NETWORKS USED FOR IMAGING SPECTRAL DATA PATTERN RECOGNITION. REMOTE SENSING FOR LAND & RESOURCES, 2004, 16(3): 23-27.