Study Findings from Chinese Academy of Sciences Broaden Understanding of Atmospheric Science (A Hybrid Neural Network Model for Enso Prediction In Combination With Principal Oscillation Pattern Analyses)

摘要

By a News Reporter-Staff News Editor at Network Daily News – Investigators publish new report on Science - Atmospheric Science. According to news originating from Qingdao, People’s Republic of China, by NewsRx correspondents, research stated, “El Nino-Southern Oscillation (ENSO) can be currently predicted reasonably well six months and longer, but large biases and uncertainties remain in its real-time prediction. Various approaches have been taken to improve understanding of ENSO processes, and different models for ENSO predictions have been developed, including linear statistical models based on principal oscillation pattern (POP) analyses, convolutional neural networks (CNNs), and so on.”