Dionisio Rodríguez-Esparragón, J. Marcello, N. M. Betancort, C. Gonzalo-Martín
{"title":"利用浅层神经网络从再分析数据估计风强度数据","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":"{\"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}","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}
Estimation of wind intensity data from reanalysis data using a shallow neural network
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.