PublisherDOIYearVolumeIssuePageTitleAuthor(s)Link
Journal of the Korean Society of Hazard Mitigation10.9798/kosham.2022.22.1.67202222167-78Application of Neural Networks to Predict Daecheong Dam Water LevelsYong Min Ryu, Eui Hoon Leehttp://j-kosham.or.kr/upload/pdf/KOSHAM-2022-22-1-67.pdf, http://j-kosham.or.kr/journal/view.php?doi=10.9798/KOSHAM.2022.22.1.67, http://j-kosham.or.kr/upload/pdf/KOSHAM-2022-22-1-67.pdf
Environmental Quality Management10.1002/tqem.21493201726355-72Application of Artificial Neural Networks to Predict Total Dissolved Solids at the Karaj DamGholamreza Asadollahfardi, Hossein Zangooei, Shiva Homayoun Aria, Elnaz Daneshhttps://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Ftqem.21493, https://onlinelibrary.wiley.com/doi/full/10.1002/tqem.21493
Journal of the American Water Resources Association10.1111/j.1752-1688.2007.00107.x20074351245-1256Field-Scale Application of Three Types of Neural Networks to Predict Ground-Water LevelsTirusew Asefa, Nisai Wanakule, Alison Adamshttps://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fj.1752-1688.2007.00107.x, http://onlinelibrary.wiley.com/wol1/doi/10.1111/j.1752-1688.2007.00107.x/fullpdf
European Journal of Soil Science10.1046/j.1365-2389.1999.00247.x1999503489-495Neural network models to predict soil water retentionE. J. W. Koekkoek, H. Booltinkhttps://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1046%2Fj.1365-2389.1999.00247.x, https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1046%2Fj.1365-2389.1999.00247.x, http://onlinelibrary.wiley.com/wol1/doi/10.1046/j.1365-2389.1999.00247.x/fullpdf
ITISE 202210.3390/engproc20220180112022An Application of Neural Networks to Predict COVID-19 Cases in ItalyLorena Saliaj, Eugenia Nissihttps://www.mdpi.com/2673-4591/18/1/11/pdf
Water10.3390/w14010034202114134Forecasting Reservoir Water Levels Using Deep Neural Networks: A Case Study of Angat Dam in the PhilippinesSebastian C. Ibañez, Carlo Vincienzo G. Dajac, Marissa P. Liponhay, Erika Fille T. Legara, Jon Michael H. Esteban, Christopher P. Monterolahttps://www.mdpi.com/2073-4441/14/1/34/pdf
10.21203/rs.3.rs-76759/v12020Application of Artificial Neural Networks to Predict Cotton Production: A Case Study in Diyarbakır Province, TurkeyNazire Mikail, Mehmet Fırat BARANhttps://www.researchsquare.com/article/rs-76759/v1, https://www.researchsquare.com/article/rs-76759/v1.html
Neural Computing and Applications10.1007/s00521-012-0945-y2012232507-518RETRACTED ARTICLE: Artificial neural networks application to predict the compressive damage of lightweight geopolymerAli Nazarihttp://link.springer.com/content/pdf/10.1007/s00521-012-0945-y.pdf, http://link.springer.com/article/10.1007/s00521-012-0945-y/fulltext.html, http://link.springer.com/content/pdf/10.1007/s00521-012-0945-y, http://link.springer.com/content/pdf/10.1007/s00521-012-0945-y.pdf
Neural Computing and Applications10.1007/s00521-020-05660-62021331812239-12239Retraction Note to: Artificial neural networks application to predict the compressive damage of lightweight geopolymerAli Nazarihttps://link.springer.com/content/pdf/10.1007/s00521-020-05660-6.pdf, https://link.springer.com/article/10.1007/s00521-020-05660-6/fulltext.html, https://link.springer.com/content/pdf/10.1007/s00521-020-05660-6.pdf
Advanced Materials Research10.4028/www.scientific.net/amr.694-697.28462013694-6972846-2849Application of Elman Neural Networks to Predict Truck’s Operating SpeedShao Bo Xie, Lang Weihttps://www.scientific.net/AMR.694-697.2846.pdf