| Flood prediction and uncertainty estimation using deep learning V Gude, S Corns, S Long Water 12 (3), 884, 2020 | 62 | 2020 |
| Evaluation of support vector machines and random forest classifiers in a real-time fetal monitoring system based on cardiotocography data V Nagendra, H Gude, D Sampath, S Corns, S Long 2017 IEEE conference on computational intelligence in bioinformatics and …, 2017 | 32 | 2017 |
| Integrated deep learning and supervised machine learning model for predictive fetal monitoring V Gude, S Corns Diagnostics 12 (11), 2843, 2022 | 9 | 2022 |
| SoS Explorer Application with Fuzzy-Genetic Algorithms to Assess an Enterprise Architecture–A Healthcare Case Study J Goldschmid, V Gude, S Corns Procedia Computer Science 185, 55-62, 2021 | 8 | 2021 |
| Agent based modeling for flood inundation mapping and rerouting V Gude, S Corns, C Dagli, S Long Procedia Computer Science 168, 170-176, 2020 | 8 | 2020 |
| A multi-level modeling approach for predicting real-estate dynamics V Gude International Journal of Housing Markets and Analysis, 2023 | 4 | 2023 |
| Flood Prediction and Uncertainty Estimation Using Deep Learning. Water 12 (3), 884 V Gude, S Corns, S Long DOI 10, w12030884, 2020 | 3 | 2020 |
| Flood Prediction and Uncertainty Estimation using Deep Learning Water V Gude, S Corns, S Long | 2 | 2020 |
| Factors Influencing ChatGpt Adoption for Product Research and Information Retrieval V Gude Journal of Computer Information Systems, 1-10, 2023 | 1 | 2023 |
| Modeling a decision support system for COVID-19 using systems dynamics and fuzzy inference V Gude Health Informatics Journal 28 (3), 14604582221120344, 2022 | 1 | 2022 |
| Optimal onsite microgrid design for net-zero energy operation in manufacturing industry MM Islam, M Rahman, F Heidari, V Gude Procedia Computer Science 185, 81-90, 2021 | 1 | 2021 |
| Predictive Deep Learning for Flood Evacuation Planning and Routing SM Corns, SK Long, J Hale, B Kanwar, V Gude Missouri. Department of Transportation. Construction and Materials Division, 2020 | 1 | 2020 |
| Computational intelligence methods for predicting fetal outcomes from heart rate patterns VNHGD Sampath Missouri University of Science and Technology, 2018 | 1 | 2018 |
| Integrated Deep Learning and Supervised Machine Learning Model for Predictive Fetal Monitoring. Diagnostics 2022, 12, 2843 V Gude, S Corns s Note: MDPI stays neutral with regard to jurisdictional claims in published …, 2022 | | 2022 |
| Using Trend Extraction and Spatial Trends to Improve Flood Modeling and Control J Hale, S Long, V Gude, S Corns Data Science, Data Visualization, and Digital Twins, 2021 | | 2021 |
| Predicting complex system behavior using hybrid modeling and computational intelligence VNHGD Sampath Missouri University of Science and Technology, 2020 | | 2020 |
| Evaluation of Support Vector Machines and Random Forest Classifiers in a Real-Time Fetal Monitoring System based on Cardiotocography Data VNHGD Sampath, S Corns, S Long Institute of Electrical and Electronics Engineers (IEEE), 2017 | | 2017 |
