A Case Study of Tidal Analysis Using Theory-Based Artificial Intelligence Techniques for Disaster Management in Taehwa River, South Korea
Monitoring tidal dynamics is imperative to disaster management because it requires a high
level of precision to avert possible dangers. Good knowledge of the physical drivers of tides …
level of precision to avert possible dangers. Good knowledge of the physical drivers of tides …
Deep learning algorithms and their fuzzy extensions for streamflow prediction in climate change framework
The present study analyzes the capability of convolutional neural network (CNN), long short-
term memory (LSTM), CNN-LSTM, fuzzy CNN, fuzzy LSTM, and fuzzy CNN-LSTM to mimic …
term memory (LSTM), CNN-LSTM, fuzzy CNN, fuzzy LSTM, and fuzzy CNN-LSTM to mimic …
Current State of Deep Learning Application to Water-related Disaster Management in Developing Countries
Availability of abundant water resources data is a great concern hindering adoption of deep
learning techniques (DL) for disaster mitigation in developing countries. However, over the …
learning techniques (DL) for disaster mitigation in developing countries. However, over the …
[PDF][PDF] related Disaster Management in Developing Countries
Availability of abundant water resources data is a great concern hindering adoption of deep
learning techniques (DL) for disaster mitigation in developing countries. However, over the …
learning techniques (DL) for disaster mitigation in developing countries. However, over the …