Dionisio Rodríguez-Esparragón, J. Marcello, N. M. Betancort, C. Gonzalo-Martín
{"title":"Estimation of wind intensity data from reanalysis data using a shallow neural network","authors":"Dionisio Rodríguez-Esparragón, J. Marcello, N. M. Betancort, C. Gonzalo-Martín","doi":"10.1109/IWOBI47054.2019.9114455","DOIUrl":null,"url":null,"abstract":"Global change is one of the outstanding problems nowadays. This is the reason why considerable attention, and economic resources to monitor climate variables have increased. Wind data constitute one of the key elements that determine the local climate. In this paper, the performance of a shallow neural net (SNN) is tested to simulate remote sensing wind intensity data from reanalysis data from nearby location. As a result, a sequence of wind data with more spatial resolution can be achieved, allowing the availability of more data at the local scale.","PeriodicalId":427695,"journal":{"name":"2019 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWOBI47054.2019.9114455","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Global change is one of the outstanding problems nowadays. This is the reason why considerable attention, and economic resources to monitor climate variables have increased. Wind data constitute one of the key elements that determine the local climate. In this paper, the performance of a shallow neural net (SNN) is tested to simulate remote sensing wind intensity data from reanalysis data from nearby location. As a result, a sequence of wind data with more spatial resolution can be achieved, allowing the availability of more data at the local scale.