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Conference Paper
A Study on Rainfall Prediction based on Meteorological Time Series
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- Authors
- KangWoon Hong, Taegyu Kang
- Issue Date
- 2021-08
- Citation
- International Conference on Ubiquitous and Future Networks (ICUFN) 2021, pp.1-3
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- This study aims to present the results of the research and development project on the urban inundation prediction technology during the heavy rain period. In this study, the results of rainfall prediction using heterogeneous weather data and machine learning are presented. In the predictive analysis of univariate time series data, it was confirmed that the CNN-LSTM model showed the best performance among several deep neural network models. In the predictive analysis of multivariate time series data, it was confirmed that the ConvLSTM model showed the best performance among several deep neural network models.
- KSP Keywords
- Best performance, Deep neural network(DNN), Development Project, Heavy rain, Multivariate time series, Neural network model, Prediction technology, Time series data, Univariate time series, machine Learning, neural network(NN)