Atmospheric and Climate Sciences

Atmospheric and Climate Sciences

ISSN Print: 2160-0414
ISSN Online: 2160-0422
www.scirp.org/journal/acs
E-mail: acs@scirp.org
"The Application of Deep Learning in Airport Visibility Forecast"
written by Lei Zhu, Guodong Zhu, Lei Han, Nan Wang,
published by Atmospheric and Climate Sciences, Vol.7 No.3, 2017
has been cited by the following article(s):
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[2] Deep learning models for visibility forecasting using climatological data
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[3] Meteorological characteristics of fog events in Korean smart cities and machine learning based visibility estimation
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[7] Temporal and Spatial Characteristics of Meteorological Elements in the Vertical Direction at Airports and Hourly Airport Visibility Prediction by Artificial Intelligence …
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[9] Analog Ensemble Forecasting System for Low-Visibility Conditions over the Main Airports of Morocco
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[10] Visibility detection and prediction of foggy highway based on lane line detection and Winters additive model
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[11] LSTM-Based Visibility Detection for Airport Images in Time Series
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[12] Efficient Resnet Model for Atmospheric Visibility Classification
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[14] LSTM 을 이용한 해양시정 예측 방법
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[15] A Transfer Learning Method for Meteorological Visibility Estimation Based on Feature Fusion Method
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[16] Experimental Evaluation of PSO Based Transfer Learning Method for Meteorological Visibility Estimation
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[17] Research on Airport Target Recognition under Low-Visibility Condition Based on Transfer Learning
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[18] Research on Forecast of Airport Visibility Based on Multivariate Statistics
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[19] Fog Prediction Using Deep Learning Models
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[20] Meteorology Visibility Estimation by Using Multi-Support Vector Regression Method
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[21] Forecasting Atmospheric Visibility Using Auto Regressive Recurrent Neural Network
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[22] Weather Variability Control in Three Colombian Airports
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[23] A comparison of datamining tools for geo-spatial estimation of visibility from AROME-Morocco model outputs in regression framework
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[24] Fog prediction using artificial intelligence: A case study in Wamena Airport
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[25] Multimodal Deep Fusion Network for Visibility Assessment with a Small Training Dataset
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[26] Research on the long-term and short-term forecasts of navigable river's water-level fluctuation based on the adaptive multilayer perceptron
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[27] Multi-step LSTM Prediction Model for Visibility Prediction
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[28] Visibility Forecast for Airport Operations by LSTM Neural Network.
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[29] Weather Visibility Prediction Based on Multimodal Fusion
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[30] VisNet: Deep Convolutional Neural Networks for Forecasting Atmospheric Visibility
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[31] Fog Image Classification and Visibility Detection Using CNN
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[32] Visibility forecast for airport operations by LSTM neural networks
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[33] Deep Learning Models for Visibility Forecasting
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[34] ПРИМЕНЕНИЕ ГЛУБОКИХ НЕЙРОННЫХ СЕТЕЙ ДЛЯ КРАТКОСРОЧНОГО ПРОГНОЗА ДАЛЬНОСТИ ВИДИМОСТИ
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[35] Peramalan Jumlah Penumpang dan Barang di Bandar Udara Internasional Juanda dan Pelabuhan Tanjung Perak Menggunakan Model Hybrid ARIMAX dan Deep …
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[36] 利用集合深度学习方法融合多源数据开发全国能见度网格数据
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[37] Deep Forecasting
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[38] Visibility Prediction Based on Kilometric NWP Model Outputs Using Machine-Learning Regression
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[39] Application of deep learning to multivariate aviation weather forecasting by long short-term memory
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