农业机械学报2017，Vol.48Issue(10)：156-164,9.DOI:10.6041/j.issn.1000-1298.2017.10.019
基于鱼群算法的极限学习机影像分类方法优化
Optimization of ELM Classification Model for Remote Sensing Image Based on Artificial Fish-swarm Algorithm
摘要
Abstract
As a new means of earth resource survey,land use change and coverage (LUCC) and ecological environment monitoring,remote sensing technology has a great advantage.The automatic classification for remote sensing image is the key technology to extract rich ground-object information and monitor the dynamic change of LUCC.Machine learning can flexibly build a model portrayed by parameters,and automatically extract information,which has been widely used in image classification because of its good robustness and convergence,and easy to be combined with other methods.Based on the study of traditional extreme learning machine (ELM) theory,the optimal selection of kernel function parameters and regularizing parameters were performed by using artificial fish swarm algorithm (AF) and the optimal ELM image classification model (AF-ELM) was constructed.The classification model used AF to optimize the wavelet kernel parameters and regularizing parameters of ELM to improve the classification accuracy.After that the classification for multi-spectral remote sensing image was implemented by using the parameter-optimized ELM classifier,meanwhile,compared with some standard classifier such as artificial neural networks (ANM),support vector machine (SVM) and extreme learning machine (ELM),and it was comparatively analyzed with the ELM polynomial kernel and RBF kernel classification algorithm.The experiments proved that optimal AF ELM classifier was more faster and accurate,which was superior to those before-mentioned classifiers.It can be used for the automatic extraction of various elements from remote sensing image.关键词
极限学习机/鱼群算法/影像分类/小波核函数/遥感影像/优化Key words
extreme learning machine/fish swarm algorithm/image classification/wavelet kernel function/remote sensing image/optimization分类
信息技术与安全科学引用本文复制引用
林怡,季昊巍,NICO Sneeuw,叶勤..基于鱼群算法的极限学习机影像分类方法优化[J].农业机械学报,2017,48(10):156-164,9.基金项目
国土资源部公益性行业科研专项(201211011)和上海市科学技术委员会科研计划项目(13231203602) （201211011）
