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Found 3 papers, 1 papers with code
Vehicle Fuel Optimization Under Real-World Driving Conditions: An Explainable Artificial Intelligence Approach
Fuel optimization of diesel and petrol vehicles within industrial fleets is critical for mitigating costs and reducing emissions.
Interpretable Machine Learning Models for Predicting and Explaining Vehicle Fuel Consumption Anomalies
Identifying anomalies in the fuel consumption of the vehicles of a fleet is a crucial aspect for optimizing consumption and reduce costs.
BIG-bench Machine Learning
Interpretable Machine Learning
+1
Rule Extraction in Unsupervised Anomaly Detection for Model Explainability: Application to OneClass SVM
In this paper, we evaluate several rule extraction techniques over OneClass SVM models, as well as present alternative designs for some of those algorithms.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
+1
