PublisherDOIYearVolumeIssuePageTitleAuthor(s)Link
The Plant Pathology Journal10.5423/ppj.nt.04.2022.00622022384395-402Optimizing Artificial Neural Network-Based Models to Predict Rice Blast Epidemics in KoreaKyung-Tae Lee, Juhyeong Han, Kwang-Hyung Kimhttp://ppjonline.org/upload/pdf/PPJ-NT-04-2022-0062.pdf, http://ppjonline.org/journal/view.php?doi=10.5423/PPJ.NT.04.2022.0062, http://ppjonline.org/upload/pdf/PPJ-NT-04-2022-0062.pdf
Innovative Infrastructure Solutions10.1007/s41062-018-0137-4201831Optimized developed artificial neural network-based models to predict the blast-induced ground vibrationAbbas Abbaszadeh Shahri, Reza Asheghihttp://link.springer.com/article/10.1007/s41062-018-0137-4/fulltext.html, http://link.springer.com/content/pdf/10.1007/s41062-018-0137-4.pdf, http://link.springer.com/content/pdf/10.1007/s41062-018-0137-4.pdf
Applied Mechanics and Materials10.4028/www.scientific.net/amm.170-173.10132012170-1731013-1016Using Artificial Neural Network to Predict Blast-Induced Ground VibrationFu Qiang Gao, Xiao Qiang Wanghttps://www.scientific.net/AMM.170-173.1013.pdf
Materials Science Forum10.4028/www.scientific.net/msf.869.5722016869572-577Artificial Neural Network Model for Predict of Silicon Content in Hot Metal Blast FurnaceSayd Farage David, Felipe Farage David, M.L.P. Machadohttps://www.scientific.net/MSF.869.572.pdf
Engineering with Computers10.1007/s00366-016-0442-52016324631-644A new combination of artificial neural network and K-nearest neighbors models to predict blast-induced ground vibration and air-overpressureMaryam Amiri, Hassan Bakhshandeh Amnieh, Mahdi Hasanipanah, Leyli Mohammad Khanlihttp://link.springer.com/content/pdf/10.1007/s00366-016-0442-5.pdf, http://link.springer.com/article/10.1007/s00366-016-0442-5/fulltext.html, http://link.springer.com/content/pdf/10.1007/s00366-016-0442-5.pdf, http://link.springer.com/content/pdf/10.1007/s00366-016-0442-5
Natural Resources Research10.1007/s11053-019-09503-72019292723-737A Novel Artificial Intelligence Approach to Predict Blast-Induced Ground Vibration in Open-Pit Mines Based on the Firefly Algorithm and Artificial Neural NetworkYonghui Shang, Hoang Nguyen, Xuan-Nam Bui, Quang-Hieu Tran, Hossein Moayedihttp://link.springer.com/content/pdf/10.1007/s11053-019-09503-7.pdf, http://link.springer.com/article/10.1007/s11053-019-09503-7/fulltext.html, http://link.springer.com/content/pdf/10.1007/s11053-019-09503-7.pdf
Advanced Applications for Artificial Neural Networks10.5772/intechopen.715362018Dynamic Factor Model and Artificial Neural Network Models: To Combine Forecasts or Combine Models?Dynamic Factor Model, Artificial N.N.M.T.C.F.o.C. Models?http://www.intechopen.com/download/pdf/58149
CLEAN - Soil, Air, Water10.1002/clen.20140011620154371002-1009Mathematical and Artificial Neural Network Models to Predict the Membrane Fouling Behavior of an Intermittently-Aerated Membrane Bioreactor Under Sub-Critical FluxZuowei Wang, Xiaohui Wuhttps://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fclen.201400116, https://onlinelibrary.wiley.com/doi/full/10.1002/clen.201400116
Applied Sciences10.3390/app12168161202212168161Multifunctional Models, Including an Artificial Neural Network, to Predict the Compressive Strength of Self-Compacting ConcreteKawan Ghaforhttps://www.mdpi.com/2076-3417/12/16/8161/pdf
Sustainability10.3390/su120101092019121109Artificial Neural Network-Based Residential Energy Consumption Prediction Models Considering Residential Building Information and User Features in South KoreaMansu Kim, Sungwon Jung, Joo-won Kanghttps://www.mdpi.com/2071-1050/12/1/109/pdf