arXiv Open Access 2024

A Database Engineered System for Big Data Analytics on Tornado Climatology

Fengfan Bian Carson K. Leung Piers Grenier Harry Pu Samuel Ning +1 lainnya
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Abstrak

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.

Topik & Kata Kunci

Penulis (6)

F

Fengfan Bian

C

Carson K. Leung

P

Piers Grenier

H

Harry Pu

S

Samuel Ning

A

Alfredo Cuzzocrea

Format Sitasi

Bian, F., Leung, C.K., Grenier, P., Pu, H., Ning, S., Cuzzocrea, A. (2024). A Database Engineered System for Big Data Analytics on Tornado Climatology. https://arxiv.org/abs/2409.17668

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Informasi Jurnal
Tahun Terbit
2024
Bahasa
en
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arXiv
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Open Access ✓