Knowledge discovery from multispectral satellite images

S. Mccaslin, A. Kulkarni
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引用次数: 3

Abstract

In this paper, we propose a method to extract and reduce fuzzy IF-THEN rules from fuzzy neural systems. After training, fuzzy rules are extracted from the fuzzy neural network by backtracking along the weighted paths through the neural network. These rules are then reduced by use of a fuzzy associative memory (FAM) bank. We used this algorithm to extract classification rules from a multi-spectral satellite image. The image represents the Mississippi river bottomland. In order to verify the rule extraction method, measures such as accuracy, overall Kappa and fidelity are used. The results are presented in the paper.
从多光谱卫星图像中发现知识
本文提出了一种从模糊神经系统中提取和约简模糊IF-THEN规则的方法。训练后,通过神经网络沿加权路径回溯,从模糊神经网络中提取模糊规则。然后通过使用模糊联想记忆(FAM)库来减少这些规则。我们利用该算法从多光谱卫星图像中提取分类规则。这幅图描绘的是密西西比河的河滩。为了验证规则提取方法,使用了精度、总体Kappa和保真度等度量。本文给出了实验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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