NDLI: Cloud Classification Based on Self-Organizing Feature Map and Probabilistic Neural Network

Content Provider	IEEE Xplore Digital Library
Author	Ren Zhang Yanlei Wang Wei Liu Weijun Zhu Jiguang Wang
Copyright Year	2006
Description	Author affiliation: Inst. of Meteorol., PLA Univ. of Sci. & Technol., Nanjing (Ren Zhang; Yanlei Wang)
Abstract	For overcoming the shortcoming of single ANN classifier being difficult used to identify and classify complex clouds, based on the multi-spectrum samples of stationary meteorology satellite cloud pictures, by computing and analysing the gray-grads and texture characters of satellite cloud picture samples, and picking-up some suitable cloud classification factors, a synthetic optimization SOM-PNN cloud classifier was designed and established. Firstly, the clouds samples were classified by SOM in the form of unsupervised, by identifying and partitioning the analogical sample-sets and getting rid of the invalid data, then the initial classification error were revised and the initial classification results were more optimized by using PNN in the form of supervised. The experiments results of cloud classification showed that the accuracy of the synthetic SOM-PNN classifier can achieved 90%, which is evidently excel to other single-statistical cloud classifier
Starting Page	41
Ending Page	45
File Size	497555
Page Count	5
File Format	PDF
ISBN	1424403324
DOI	10.1109/WCICA.2006.1712358
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Clouds Neural networks Satellites Meteorology Programmable logic arrays Electronic mail Information science Educational institutions Design engineering Artificial neural networks cloud classification self-organizing feature map(SOM) probabilistic neural network(PNN) satellite cloud picture
Content Type	Text
Learning Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Mr. Siddhartha Mukherjee siddhartha@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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