A Database Engineered System for Big Data Analytics on Tornado Climatology
<|reference_start|>A Database Engineered System for Big Data Analytics on Tornado Climatology: Recognizing the challenges with current tornado warning systems, we investigate alternative approaches. In particular, we present a database engi-neered system that integrates information from heterogeneous rich data sources, including climatology data for tornadoes and data just before a tornado warning. The system aids in predicting tornado occurrences by identifying the data points that form the basis of a tornado warning. Evaluation on US data highlights the advantages of using a classification forecasting recurrent neural network (RNN) model. The results highlight the effectiveness of our database engineered system for big data analytics on tornado climatology-especially, in accurately predict-ing tornado lead-time, magnitude, and location, contributing to the development of sustainable cities.<|reference_end|>
@article{bian2024a,
    title={A Database Engineered System for Big Data Analytics on Tornado
  Climatology},
    author={Fengfan Bian, Carson K. Leung, Piers Grenier, Harry Pu, Samuel Ning,
  Alfredo Cuzzocrea},
    journal={arXiv preprint arXiv:2409.17668},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.17668},
    primaryClass={cs.DB}
}