Lightning prediction using satellite atmospheric sounding data and feed-forward artificial neural network-Reference-Cited by-同舟云学术

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Lightning prediction using satellite atmospheric sounding data and feed-forward artificial neural network

Published:2017-06-22 Issue:1 Volume:33 Page:79-92
ISSN:1064-1246
Container-title:Journal of Intelligent & Fuzzy Systems
language:
Short-container-title:IFS

Author:

Alves Elton Rafael¹,Tavares da Costa Carlos¹,Lopes Márcio Nirlando Gomes²,da Rocha Brígida Ramati Pereira¹²,de Sá José Alberto Silva³

Affiliation:

1. Graduate Program in Electrical Engineering, Federal University of Pará, Rua Augusto Corrêa, Guamá, Belém, Pará, Brazil

2. Operations and Management Center of the Amazonian Protection System, Avenida Júlio Cesar, Val-de-Cans, Belém, Pará, Brazil

3. Center of Natural Sciences and Technology, Pará State University, Travessa Doutor Enéas Pinheiro, Marco, Belém, Pará, Brazil

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference42 articles.

1. Sounding-derived indices for neural network based short-term thunderstorm and rainfall forecast;Manzato;Atmospheric Research,2007

2. An experimental study of the remote location of lightning flashes using a VLF arrival time difference technique, Quart;Lee;J R Met Soc,1986

3. A stability index for forecasting thunderstorms;Showalter;Bull Amer Meteor Soc,1947

4. Receiver operating characteristic (ROC) analysis: Basic principles and applications in radiology;Erkel;European Journal of Radiology,1998

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1. Performance Analysis Among Predictive Models of Lightning Occurrence Using Artificial Neural Networks and SMOTE;IEEE Latin America Transactions;2021-05

2. Pre-estimation of Distance-Based Lightning Using Effective Meteorological Parameters;Arabian Journal for Science and Engineering;2021-01-05

3. Frontiers in Lightning Research and Opportunities for Scientists from Developing Countries;Lecture Notes in Electrical Engineering;2021

4. Lightning incidence over the southeastern microregion of Para State, Brazil;2019 International Symposium on Lightning Protection (XV SIPDA);2019-09

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