13 citations as recorded by crossref.

1. The Role of Weather Radar in Rainfall Estimation and Its Application in Meteorological and Hydrological Modelling—A Review Z. Sokol et al. 10.3390/rs13030351
2. The 3D Neural Network for Improving Radar-Rainfall Estimation in Monsoon Climate N. Roslan et al. 10.3390/atmos12050634
3. Modelling Precipitation Intensities from X-Band Radar Measurements Using Artificial Neural Networks—A Feasibility Study for the Bavarian Oberland Region S. Vogl et al. 10.3390/w14030276
4. Improving radar estimates of rainfall using an input subset of artificial neural networks T. Yang et al. 10.1117/1.JRS.10.026013
5. Error modeling and hierarchical Bayesian fusion for spaceborne and ground radar rainfall data L. Kou et al. 10.1016/j.jhydrol.2023.130599
6. A neural network-based local rainfall prediction system using meteorological data on the Internet: A case study using data from the Japan Meteorological Agency T. Kashiwao et al. 10.1016/j.asoc.2017.03.015
7. Predicting streamflows to a multipurpose reservoir using artificial neural networks and regression techniques M. Hassan et al. 10.1007/s12145-014-0161-7
8. Optimization of X-Band Radar Rainfall Retrieval in the Southern Andes of Ecuador Using a Random Forest Model J. Orellana-Alvear et al. 10.3390/rs11141632
9. Merging dual-polarization X-band radar network intelligence for improved microscale observation of summer rainfall in south Sweden S. Hosseini et al. 10.1016/j.jhydrol.2023.129090
10. Three-dimensional fusion of spaceborne and ground radar reflectivity data using a neural network-based approach L. Kou et al. 10.1007/s00376-017-6334-9
11. Development of streamflow prediction models for a weir using ANN and step-wise regression M. Hassan et al. 10.1007/s40808-018-0500-7
12. Observation and analysis of atmospheric rainfall based on the very high frequency radar H. Qing et al. 10.1049/iet-rsn.2016.0089
13. Artificial neural network and regressed beam-column connection explicit mathematical moment-rotation expressions A. Kueh 10.1016/j.jobe.2021.103195