Wind ambiguity removal by the use of neural network techniques-Reference-Cited by-同舟云学术

Wind ambiguity removal by the use of neural network techniques

Published:1991 Issue:C11 Volume:96 Page:20521
ISSN:0148-0227
Container-title:Journal of Geophysical Research
language:en
Short-container-title:J. Geophys. Res.

Author:

Badran F.,Thiria S.,Crepon M.

Publisher

American Geophysical Union (AGU)

Subject

Paleontology,Space and Planetary Science,Earth and Planetary Sciences (miscellaneous),Atmospheric Science,Earth-Surface Processes,Geochemistry and Petrology,Soil Science,Water Science and Technology,Ecology,Aquatic Science,Forestry,Oceanography,Geophysics

Link

http://www.agu.org/journals/jc/v096/iC11/91JC02216/91JC02216.pdf

Reference29 articles.

1. Aarts, E., , J., Korst, , Simulated Annealing and Boltzmann Machines, John Wiley, New York, 1989,

2. The effect of model resolution and satellite sounding data on GLAS model forecasts;Atlas;Mon. Weather Rev.,1982

3. A method to de-alias the scatterometer wind field: a real world application;Badran,1989

4. Speech, pattern discrimination and multilayer perceptrons;Bourlard;Comput. Speech and Language,1989

5. ERS-1 wind scatterometer: Wind extraction and ambiguity removal;Cavanie,1986

Cited by 22 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Estimating Daily Temperatures over Andhra Pradesh, India, Using Artificial Neural Networks;Atmosphere;2023-09-28

2. Neural Network-Based Wind Measurements in Rainy Conditions Using the HY-2A Scatterometer;Remote Sensing;2023-09-04

3. Deep learning, explained: Fundamentals, explainability, and bridgeability to process-based modelling;Environmental Modelling & Software;2021-10

4. A Neural Network Approach to Improve the Vertical Resolution of Atmospheric Temperature Profiles From Geostationary Satellites;IEEE Geoscience and Remote Sensing Letters;2013-01

5. Application of Artificial Neural Networks for Sea-Surface Wind-Speed Retrieval From IRS-P4 (MSMR) Brightness Temperature;IEEE Geoscience and Remote Sensing Letters;2010-07