Spatial predictive mapping using artificial neural networks

8 citations as recorded by crossref.

1. Using Artificial Neural Networks and Remotely Sensed Data to Evaluate the Relative Importance of Variables for Prediction of Within-Field Corn and Soybean Yields A. Kross et al. https://doi.org/10.3390/rs12142230
2. Alteration zone mapping in tropical region: A comparison between data-driven and knowledge-driven techniques P. Mahanta & S. Maiti https://doi.org/10.1007/s12040-024-02386-0
3. Omics-driven plant breeding through phenomics-enviromics crosstalk H. Li et al. https://doi.org/10.1038/s41467-026-73097-x
4. Evaluating healthcare access in informal settlements using satellites and neural networks I. Pal & A. Petkar https://doi.org/10.1680/jsmic.21.00006
5. Multi-task learning for data-efficient spatiotemporal modeling of tool surface progression in ultrasonic metal welding H. Chen et al. https://doi.org/10.1016/j.jmsy.2020.12.009
6. Surface movement above an underground coal longwall mine after closure A. Vervoort https://doi.org/10.5194/nhess-16-2107-2016
7. Zoning Suitable Land for the Cultivation of Rice, Wheat, and Barley by Integration of Artificial Intelligent Methods and Spatial Data N. Bagheri et al. https://doi.org/10.1007/s40003-023-00686-3
8. Combining Artificial Neural Networks and GIS Fundamentals for Coastal Erosion Prediction Modeling A. Peponi et al. https://doi.org/10.3390/su11040975