首页|Zhengzhou University Reports Findings in Machine Learning (Research on machine l earning hybrid framework by coupling grid-based runoff generation model and runo ff process vectorization for flood forecasting)
Zhengzhou University Reports Findings in Machine Learning (Research on machine l earning hybrid framework by coupling grid-based runoff generation model and runo ff process vectorization for flood forecasting)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news originating from Zhengzhou, People’s Re public of China, by NewsRx correspondents, research stated, “One of the importan t non-engineering measures for flood forecasting and disaster reduction in water sheds is the application of machine learning flood prediction models, with Long Short-Term Memory (LSTM) being one of the most representative time series predic tion models. However, the LSTM model has issues of underestimating peak flows an d poor robustness in flood forecasting applications.”
ZhengzhouPeople’s Republic of ChinaA siaCyborgsEmerging TechnologiesMachine Learning
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