查看更多>>摘要：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 reporting originating from Nanjing,Peo ple's Republic of China,by NewsRx correspondents,research stated,"A novel con volutional neural network-long short-term memory (CNN-LSTM) model is proposed fo r wave height prediction. The model effectively extracts relevant features such as wind speed,wind direction,wave height,latitude,and longitude." Financial supporters for this research include National Key Research and Develop ment Program of China,Jiangsu Province Marine Technology Innovation Program,Ch ina,Nantong Social Livelihood Science and Technology Plan Projects,China. Our news editors obtained a quote from the research from Hohai University,"The proposed model outperforms traditional machine learning algorithms such as multi -layer perceptron (MLP),support vector machine (SVM),random forest and LSTM,e specially for extreme values and fluctuations. The model has a significantly low er average root mean square error (RMSE) of 71.1%,72.8% ,71.9% and 72.2% for MLP,SVM,random forest and LS TM,respectively. Our model is computationally more efficient than traditional n umerical simulations,making it suitable for real-time applications. Moreover,i t has better long-term robustness compared to traditional models. The integratio n of CNN and LSTM techniques improves wave height prediction accuracy while enha ncing its efficiency and robustness. The proposed CNN-LSTM model provides a prom ising tool for effective wave height prediction,making a valuable contribution to coastal disaster prevention and mitigation. Future research should aim to imp rove long-term prediction accuracy,and we believe that the CNN-LSTM model plays a crucial role in developing real-time coastal disaster prevention and mitigati on measures."
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