摘要
机器人与机器学习的新闻编辑每日新闻-机器学习的新研究是一篇报道的主题。据《中国人民日报郑州消息》报道，NewsRx记者的研究表明，“应用机器学习洪水预报模型是流域防洪减灾的重要非工程措施之一，长短期记忆(LSTM)是最具代表性的时间序列预报模型之一。LSTM模型在洪水预测应用中存在低估峰值流量和鲁棒性差的问题。
Abstract
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.”
NETL
NSTL