Public Use Cases in Industry & R&D
Our Use Cases present the results of XTRACTIS modeling and include complete Benchmarks against Neural Networks, Boosted Trees, Random Forests, and Logistic Regression.
These studies illustrate the ability of XTRACTIS to automatically induce knowledge in the form of predictive and intelligible mathematical relationships from real-world data (public data or authorized private data).
For each application, we show how the induced décision system uses its fuzzy rules to compute explained predictions for new situations, i.e. unknown to the learning data set.
UC#21 - Release: Oct. 2023 | Update: Feb. 2024
UC#18 - Release: Jun. 2023 | Update: Jan. 2024
UC#15 - Release: Mar. 2023 | Update: Mar. 2024
Design an AI-based decision system that accurately predicts the upcoming risk of underwater pipes rupture considering the apparent complexity of the phenomenon, to plan rational maintenance operations.
UC#13 - Release: Feb. 2023 | Update: Feb. 2024
UC#02 - Release: Aug. 2022 | Update: Mar. 2024
Discovery of effective emergency braking strategies from different driving situations to design an EBA that assists the driver by triggering automatically the ABS, while being able to explain each decision offline.