Gustavo Furquim

A Distributed Approach to Flood Prediction Using a WSN and ML: A Comparative Study of ML Techniques in a WSN Deployed in Brazil

Jo Ueyama, Eduardo M. Mendiondo, Gustavo Pessin, 2015, IDEAL.

Improving the accuracy of a flood forecasting model by means of machine learning and chaos theory

Jo Ueyama, Eduardo M. Mendiondo, Gustavo Pessin, 2015, Neural Computing and Applications.

Combining Wireless Sensor Networks and Machine Learning for Flash Flood Nowcasting

Torsten Braun, Jo Ueyama, João Porto de Albuquerque, 2014, 2014 28th International Conference on Advanced Information Networking and Applications Workshops.

An Accurate Flood Forecasting Model Using Wireless Sensor Networks and Chaos Theory: A Case Study with Real WSN Deployment in Brazil

Jo Ueyama, Eduardo M. Mendiondo, Gustavo Pessin, 2014, EANN.

How to Improve Fault Tolerance in Disaster Predictions: A Case Study about Flash Floods Using IoT, ML and Real Data

Richard Werner Nelem Pazzi, Jo Ueyama, Geraldo P. R. Filho, 2018, Sensors.

Exploiting Evolution on UAV Control Rules for Spraying Pesticides on Crop Fields

André Carlos Ponce de Leon Ferreira de Carvalho, Jo Ueyama, Geraldo P. R. Filho, 2014, EANN.

Fine-Tuning of UAV Control Rules for Spraying Pesticides on Crop Fields

André Carlos Ponce de Leon Ferreira de Carvalho, Jo Ueyama, Geraldo P. R. Filho, 2014, 2014 IEEE 26th International Conference on Tools with Artificial Intelligence.