基于人工神经网络的GMS云图四类云系的识别

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基于人工神经网络的GMS云图四类云系的识别

白慧卿, 方宗义, 吴蓉璋, 郑君里

文章导航 > 应用气象学报 > 1998 > 9(4): 402-409

白慧卿, 方宗义, 吴蓉璋, 等. 基于人工神经网络的GMS云图四类云系的识别. 应用气象学报, 1998, 9(4): 402-409..

引用本文:

白慧卿, 方宗义, 吴蓉璋, 等. 基于人工神经网络的GMS云图四类云系的识别. 应用气象学报, 1998, 9(4): 402-409.

Bai Huiqing, Fang Zongyi, Wu Rongzhang, et al. Identification about four kinds of cloud systems in gms images based on neural network. J Appl Meteor Sci, 1998, 9(4): 402-409.

Citation:

Bai Huiqing, Fang Zongyi, Wu Rongzhang, et al. Identification about four kinds of cloud systems in gms images based on neural network. J Appl Meteor Sci, 1998, 9(4): 402-409.

白慧卿, 方宗义, 吴蓉璋, 等. 基于人工神经网络的GMS云图四类云系的识别. 应用气象学报, 1998, 9(4): 402-409..

引用本文:

白慧卿, 方宗义, 吴蓉璋, 等. 基于人工神经网络的GMS云图四类云系的识别. 应用气象学报, 1998, 9(4): 402-409.

Bai Huiqing, Fang Zongyi, Wu Rongzhang, et al. Identification about four kinds of cloud systems in gms images based on neural network. J Appl Meteor Sci, 1998, 9(4): 402-409.

Citation:

Bai Huiqing, Fang Zongyi, Wu Rongzhang, et al. Identification about four kinds of cloud systems in gms images based on neural network. J Appl Meteor Sci, 1998, 9(4): 402-409.

基于人工神经网络的GMS云图四类云系的识别

1.
国家卫星气象中心，清华大学电子工程系

中图分类号: P455
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出版历程
- 刊出日期: 1998-11-30

Identification About Four Kinds of Cloud Systems in GMS Images Based on Neural Network

1.
1) (National Satellite Meteorological Center, Beijing 100081); 2) (Department of Electronic Engineering, Tsinghua University, Beijing 100084)

摘要: 应用人工神经网络方法较成功地识别了GMS云图中的四类云系，并与传统的统计识别方法进行了对比，得出结论：神经网络方法更适合于云系的特征识别。还研究了神经网络本身的问题，取得一些网络设计的经验。
- 神经网络;
- 云系;
- 识别
Abstract: Based on the theory of neural network, four kinds of cloud systems in GMS images are successfully identified. Comparing neural network with traditional maximum likelihood method, we can draw the conclusion that the neural network is even better for identifying cloud systems. Some problems about neural network itself are also studied, and some experiences for designing neural network are obtained.
- Neural network;
- Cloud system;
- Identification

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摘要浏览量: 3481
HTML全文浏览量: 241
PDF下载量: 1773
被引次数: 0

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