comparison of different neural network approaches for the tropospheric profiling over the inter-tropical lands using gps radio occultation data对流层不同的神经网络方法的比较分析在inter-tropical土地使用gps无线电掩星数据.pdfVIP
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comparison of different neural network approaches for the tropospheric profiling over the inter-tropical lands using gps radio occultation data对流层不同的神经网络方法的比较分析在inter-tropical土地使用gps无线电掩星数据
Algorithms 2009, 2, 31-45; doi:10.3390/a2010031 OPEN ACCESS algorithms ISSN 1999-4893 /algorithms Article Comparison of Different Neural Network Approaches for the Tropospheric Profiling over the Inter-tropical Lands Using GPS Radio Occultation Data Stefania Bonafoni *, Fabrizio Pelliccia and Roberta Anniballe Dept. of Electronic and Information Engineering, University of Perugia, via G. Duranti 93, 06125 Perugia, Italy, Ph. +390755853663, Fax +390755853654 E-mail: stefania.bonafoni@diei.unipg.it; fabrizio.pelliccia@diei.unipg.it; robertaanniballe@jumpy.it * Author to whom correspondence should be addressed. Received: 9 December 2008; in revised form: 12 January 2009 / Accepted: 14 January 2009 / Published: 20 January 2009 Abstract: In this study different approaches based on multilayer perceptron neural networks are proposed and evaluated with the aim to retrieve tropospheric profiles by using GPS radio occultation data. We employed a data set of 445 occultations covering the land surface within the Tropics, split into desert and vegetation zone. The neural networks were trained with refractivity profiles as input computed from geometrical occultation parameters provided by the FORMOSAT-3/COSMIC satellites, while the targets were the dry and wet refractivity profiles and the dry pressure profiles obtained from the contemporary European Centre for Medium-Range Weather Forecast data. Such a new retrieval algorithm was chosen to solve the atmospheric profiling problem with
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