scholarly journals Evaporation Duct Height Nowcasting in China’s Yellow Sea Based on Deep Learning

2021 ◽  
Vol 13 (8) ◽  
pp. 1577
Author(s):  
Jie Han ◽  
Jia-Ji Wu ◽  
Qing-Lin Zhu ◽  
Hong-Guang Wang ◽  
Yu-Feng Zhou ◽  
...  
Keyword(s):  
Deep Learning ◽  
Time Resolution ◽  
Yellow Sea ◽  
Forecast Accuracy ◽  
The Yellow Sea ◽  
Evaporation Duct ◽  
Novel Approach ◽  
Deep Learning Network ◽  
Evaporation Duct Height ◽  
Working Parameters

The evaporation duct is a weather phenomenon that often occurs in marine environments and affects the operation of shipborne radar. The most important evaluation parameter is the evaporation duct height (EDH). Forecasting the EDH and adjusting the working parameters and modes of the radar system in advance can greatly improve radar performance. Traditionally, short-term forecast methods have been used to estimate the EDH, which are characterized by low time resolution and poor forecast accuracy. In this study, a novel approach for EDH nowcasting is proposed based on the deep learning network and EDH data measured in the Yellow Sea, China. The factors that affect nowcasting were analyzed. The time resolution and forecast time were 5 min and 0–2 h, respectively. The results show that our proposed method has a higher forecast accuracy than traditional time series forecasting methods and confirm its feasibility and effectiveness.

scholarly journals Deep Learning Classification of Face Images with varying Illumination Conditions

2019 ◽  
Vol 3 (3) ◽  
Author(s):  
Chinedu Godswill Olebu ◽  
Jide Julius Popoola ◽  
Michael Rotimi Adu ◽  
Yekeen Olajide Olasoji ◽  
Samson Adenle Oyetunji
Keyword(s):  
Deep Learning ◽  
Azimuthal Angle ◽  
Recognition System ◽  
Linear Filters ◽  
Learning Network ◽  
Anisotropic Diffusion Filter ◽  
Face Images ◽  
Novel Approach ◽  
Deep Learning Network

In face recognition system, the accuracy of recognition is greatly affected by varying degree of illumination on both the probe and testing faces. Particularly, the changes in direction and intensity of illumination are two major contributors to varying illumination. In overcoming these challenges, different approaches had been proposed. However, the study presented in this paper proposes a novel approach that uses deep learning, in a MATLAB environment, for classification of face images under varying illumination conditions. One thousand one hundred (1100) face images employed were obtained from Yale B extended database. The obtained face images were divided into ten (10) folders. Each folder was further divided into seven (7) subsets based on different azimuthal angle of illumination used. The images obtained were filtered using a combination of linear filters and anisotropic diffusion filter. The filtered images were then segmented into light and dark zones with respect to the azimuthal and elevation angles of illumination. Eighty percent (80%) of the images in each subset which forms the training set, were used to train the deep learning network while the remaining twenty percent (20%), which forms the testing set, were used to test the accuracy of classification of the deep learning network generated. With three successive iterations, the performance evaluation results showed that the classification accuracy varies from 81.82% to 100.00%.   

An Evaporation Duct Height Prediction Method Based on Deep Learning

2018 ◽  
Vol 15 (9) ◽  
pp. 1307-1311 ◽  
Author(s):  
Xiaoyu Zhu ◽  
Jincai Li ◽  
Min Zhu ◽  
Zhuhui Jiang ◽  
Yinglun Li
Keyword(s):  
Deep Learning ◽  
Prediction Method ◽  
Evaporation Duct ◽  
Height Prediction ◽  
Evaporation Duct Height

Structure and distribution of fish resources in the Yellow Sea off Shandong during spring and autumn 2006

2013 ◽  
Vol 18 (6) ◽  
pp. 1335-1342
Author(s):  
Zhenbo LU ◽  
Bingqing XU ◽  
Fan LI ◽  
Mingyi SONG ◽  
Huanjun ZHANG ◽  
...  
Keyword(s):  
Yellow Sea ◽  
The Yellow Sea ◽  
Fish Resources ◽  
Distribution Of Fish

GEOLOGICAL FEATURES AND FORMING MECHANISM OF THE YELLOW SEA BASIN

2011 ◽  
Vol 31 (5) ◽  
pp. 73-78
Author(s):  
Huijun LI ◽  
Xunhua ZHANG ◽  
Shuyin NIU ◽  
Kaining YU ◽  
Aiqun SUN ◽  
...  
Keyword(s):  
Yellow Sea ◽  
The Yellow Sea ◽  
Forming Mechanism ◽  
Geological Features

Morphology of seven Collichthys lucidus populations near the coast of the Yellow Sea and East China Sea

2018 ◽  
Vol 25 (3) ◽  
pp. 576 ◽  
Author(s):  
Shuzhang LIANG ◽  
Wei SONG ◽  
Ming ZHAO ◽  
Wei CHEN ◽  
Yu LI ◽  
...  
Keyword(s):  
East China Sea ◽  
Yellow Sea ◽  
The Yellow Sea ◽  
East China ◽  
China Sea ◽  
Collichthys Lucidus
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