<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Pareto 前沿 on LiuYang Lab</title><link>https://jaywillow0.github.io/tags/pareto-%E5%89%8D%E6%B2%BF/</link><description>Recent content in Pareto 前沿 on LiuYang Lab</description><generator>Hugo</generator><language>zh-CN</language><copyright>© 2026 LiuYang</copyright><lastBuildDate>Fri, 07 Aug 2026 23:17:08 +0800</lastBuildDate><atom:link href="https://jaywillow0.github.io/tags/pareto-%E5%89%8D%E6%B2%BF/index.xml" rel="self" type="application/rss+xml"/><item><title>从昂贵仿真到Pareto前沿，一套可复用的LFP电池代理优化方法</title><link>https://jaywillow0.github.io/wechat/lfp-surrogate-pareto-optimization/</link><pubDate>Fri, 07 Aug 2026 23:17:08 +0800</pubDate><guid>https://jaywillow0.github.io/wechat/lfp-surrogate-pareto-optimization/</guid><description>&lt;p&gt;围绕比能量与比功率的权衡，梳理高保真模型、代理模型、多目标寻优和物理回代验证组成的工程闭环。&lt;/p&gt;</description></item></channel></rss>