<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>LSTM on NWP &amp; NNN</title><link>https://dhkim.info/tags/LSTM/</link><description>Recent content in LSTM on NWP &amp; NNN</description><generator>Hugo -- gohugo.io</generator><language>ko-kr</language><copyright>© 2026 김동훈</copyright><lastBuildDate>Thu, 15 Feb 2024 00:00:00 +0000</lastBuildDate><atom:link href="https://dhkim.info/tags/LSTM/index.xml" rel="self" type="application/rss+xml"/><item><title>Improved prediction of extreme ENSO events using an artificial neural network with weighted loss functions</title><link>https://dhkim.info/2024/02/ENSO_WeightedLoss/</link><pubDate>Thu, 15 Feb 2024 00:00:00 +0000</pubDate><guid>https://dhkim.info/2024/02/ENSO_WeightedLoss/</guid><description>가중 손실함수로 엘니뇨·라니냐 극값의 예측 성능을 끌어올린 연구. 2024년 Frontiers in Marine Science에 실린 논문 전문입니다.</description></item></channel></rss>