Hybrid ConvLSTM Model for Wind Speed Prediction: A Case Study for India's Highest Wind Speed Cities

MakaleAçık Erişim
  • SDG 9 · Sanayi, Yenilikçilik ve Altyapı
  • SDG 11 · Sürdürülebilir Şehirler ve Topluluklar
  • SDG 13 · İklim Eylemi

Özet

Wind speed prediction is very important for logistics, energy production and renewable energy sources, aviation and maritime, agriculture, disaster management, environmental monitoring, construction, life planning and economic activities. In this study, it was aimed to predict the wind speeds of Jaisalmer, Kochi, Mangalore, Puri and Rameswaram, which are among the cities with the highest wind speeds in India. ConvLSTM hybrid model was developed by taking advantage of the effective features of CNN and LSTM models for wind speed prediction. With ConvLSTM, it is aimed to better determine the dynamics of wind speed by processing spatial and temporal data simultaneously. ConvLSTM has been extensively tested using an approximately 15-year hourly dataset consisting of RF, SVM, ANFIS, CNN and LSTM and wind speed measurements at 10 meters and 100 meters’ altitudes. Experimental results show that ConvLSTM has R2 values above 0.9 for almost all of the city and wind speed parameters, and outperforms the compared models with the lowest error values in terms of RMSE and MAE error metrics.

Anahtar Kelimeler

RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/munzur/6264Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.18586/msufbd.1561443Yayıncı resmi DOI adresi
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1
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dc.contributor.authorUtku, Anıl
dc.contributor.authorAkyol, Sinem
dc.date.accessioned2026-10-28T15:11:26.631947467Z
dc.date.available2026-10-28T15:11:26.631947467Z
dc.date.issued2024
dc.description.abstractWind speed prediction is very important for logistics, energy production and renewable energy sources, aviation and maritime, agriculture, disaster management, environmental monitoring, construction, life planning and economic activities. In this study, it was aimed to predict the wind speeds of Jaisalmer, Kochi, Mangalore, Puri and Rameswaram, which are among the cities with the highest wind speeds in India. ConvLSTM hybrid model was developed by taking advantage of the effective features of CNN and LSTM models for wind speed prediction. With ConvLSTM, it is aimed to better determine the dynamics of wind speed by processing spatial and temporal data simultaneously. ConvLSTM has been extensively tested using an approximately 15-year hourly dataset consisting of RF, SVM, ANFIS, CNN and LSTM and wind speed measurements at 10 meters and 100 meters’ altitudes. Experimental results show that ConvLSTM has R2 values above 0.9 for almost all of the city and wind speed parameters, and outperforms the compared models with the lowest error values in terms of RMSE and MAE error metrics.
dc.identifier.doi10.18586/msufbd.1561443
dc.identifier.eissn2149-6455
dc.identifier.endpage215
dc.identifier.issn2147-7930
dc.identifier.issue2
dc.identifier.startpage201
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/munzur/6264
dc.identifier.volume12
dc.language.isotr
dc.relation.ispartofMuş Alparslan Üniversitesi Fen Bilimler Dergisi
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectMühendislik, Elektrik ve Elektronik
dc.subjectBilgisayar Bilimleri, Yapay Zeka
dc.titleHybrid ConvLSTM Model for Wind Speed Prediction: A Case Study for India's Highest Wind Speed Cities
dc.typeArticle
rdl.citation.openalex1
rdl.citation.trdizin1
rdl.oa.statusgold
rdl.oa.urlhttps://doi.org/10.18586/msufbd.1561443
rdl.sdgSDG13
rdl.sdgSDG11
rdl.sdgSDG09
rdl.source.indexTRDIZIN