<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[qq_36623004的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/qq_36623004</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; qq_36623004]]></copyright><item><title><![CDATA[conda 安装/删除/选择环境语句]]></title><link>https://blog.youkuaiyun.com/qq_36623004/article/details/127131194</link><guid>https://blog.youkuaiyun.com/qq_36623004/article/details/127131194</guid><author>qq_36623004</author><pubDate>Fri, 12 May 2023 15:50:40 +0800</pubDate><description><![CDATA[安装tf_gpu pip install tensorflow-gpu==2.5.0 -i http://pypi.douban.com/simple --trusted-host pypi.douban.com。配置镜像源  conda config --env --add channels https://mirrors.ustc.edu.cn/anaconda/pkgs/free/删除环境   conda remove -n 要删除的环境名称 --all。查看环境下的包  conda list。]]></description><category></category></item><item><title><![CDATA[CondaHTTPError:HTTP 000 CONNECTION FAILED for url＜https://mirrors.tuna.tsinghua.edu.cn/anaco解决问题]]></title><link>https://blog.youkuaiyun.com/qq_36623004/article/details/130095220</link><guid>https://blog.youkuaiyun.com/qq_36623004/article/details/130095220</guid><author>qq_36623004</author><pubDate>Tue, 11 Apr 2023 22:51:37 +0800</pubDate><description><![CDATA[我的问题是即便是删除电脑c盘中用户下的.condarc文件,当进入自己配的环境中查看镜像源时候还是有镜像，想了好久，最后去anaconda安装目录下看了下，里面也有.condarc文件，之后我又好奇看了anaconda目录envs文件中我的pytorch环境文件夹，果然里面也有.condarc我就剪切到外面了，最后果然好使，镜像删除干净了。删除镜像源，以上面配置的镜像源为例，删除其它镜像源channels后面的都要有更改。，如果是代理问题，应该会报错中有proxy单词。这里先堆上镜像源的一些代码吧！]]></description><category></category></item><item><title><![CDATA[Colorbar右侧添加箭头指向(如何去掉colorbar刻度)]]></title><link>https://blog.youkuaiyun.com/qq_36623004/article/details/129648920</link><guid>https://blog.youkuaiyun.com/qq_36623004/article/details/129648920</guid><author>qq_36623004</author><pubDate>Sun, 19 Mar 2023 12:18:39 +0800</pubDate><description><![CDATA[如何通过ax.annotate() 方法在colorbar右侧添加箭头]]></description><category></category></item><item><title><![CDATA[二维列表转换为dateframe(行列转换)]]></title><link>https://blog.youkuaiyun.com/qq_36623004/article/details/129630255</link><guid>https://blog.youkuaiyun.com/qq_36623004/article/details/129630255</guid><author>qq_36623004</author><pubDate>Fri, 17 Mar 2023 23:36:44 +0800</pubDate><description><![CDATA[二维列表转换为dateframe(行列转换)
这里定义了一个包含11个元素的二维列表，每个元素都是一个包含1个浮点数的一维列表。即该列表表示11行1列的浮点数数据。]]></description><category></category></item><item><title><![CDATA[Python 求相邻两点围成的面积]]></title><link>https://blog.youkuaiyun.com/qq_36623004/article/details/129405220</link><guid>https://blog.youkuaiyun.com/qq_36623004/article/details/129405220</guid><author>qq_36623004</author><pubDate>Wed, 08 Mar 2023 16:17:58 +0800</pubDate><description><![CDATA[Python 求相邻两点围成的面积]]></description><category></category></item><item><title><![CDATA[关于from . import _imaging as core ImportError: DLL load failed: 找不到指定的模块]]></title><link>https://blog.youkuaiyun.com/qq_36623004/article/details/129355140</link><guid>https://blog.youkuaiyun.com/qq_36623004/article/details/129355140</guid><author>qq_36623004</author><pubDate>Mon, 06 Mar 2023 09:42:34 +0800</pubDate><description><![CDATA[from . import _imaging as core ImportError: DLL load failed: 找不到指定的模块]]></description><category></category></item><item><title><![CDATA[Python plt.text定位]]></title><link>https://blog.youkuaiyun.com/qq_36623004/article/details/129352033</link><guid>https://blog.youkuaiyun.com/qq_36623004/article/details/129352033</guid><author>qq_36623004</author><pubDate>Sun, 05 Mar 2023 22:05:42 +0800</pubDate><description><![CDATA[plt.text()函数用于在图表中添加文本注释。其中，x和y参数用于指定文本注释的位置，可以通过设置这两个参数来控制文本注释的定位。]]></description><category></category></item><item><title><![CDATA[python 控制 matplotlib 图表的边框\坐标轴]]></title><link>https://blog.youkuaiyun.com/qq_36623004/article/details/129351505</link><guid>https://blog.youkuaiyun.com/qq_36623004/article/details/129351505</guid><author>qq_36623004</author><pubDate>Sun, 05 Mar 2023 21:31:52 +0800</pubDate><description><![CDATA[python 控制 matplotlib 图表的边框\坐标轴，可以通过 spines 属性来控制 matplotlib 图表的边框]]></description><category></category></item><item><title><![CDATA[win11下安装Cuda和Cudnn(pytorch+GPU环境安装)，保姆级教程！！！]]></title><link>https://blog.youkuaiyun.com/qq_36623004/article/details/127228147</link><guid>https://blog.youkuaiyun.com/qq_36623004/article/details/127228147</guid><author>qq_36623004</author><pubDate>Sun, 09 Oct 2022 17:09:50 +0800</pubDate><description><![CDATA[cuda+cudnn的安装配置(pytorch+GPU环境安装)]]></description><category></category></item><item><title><![CDATA[google 浏览器同步]]></title><link>https://blog.youkuaiyun.com/qq_36623004/article/details/127136992</link><guid>https://blog.youkuaiyun.com/qq_36623004/article/details/127136992</guid><author>qq_36623004</author><pubDate>Sat, 01 Oct 2022 20:38:17 +0800</pubDate><description><![CDATA[谷歌同步, 标签同步]]></description><category></category></item><item><title><![CDATA[导处参考文献字段代表意思]]></title><link>https://blog.youkuaiyun.com/qq_36623004/article/details/125826751</link><guid>https://blog.youkuaiyun.com/qq_36623004/article/details/125826751</guid><author>qq_36623004</author><pubDate>Sun, 17 Jul 2022 00:11:20 +0800</pubDate><description><![CDATA[引用或管理参文献时候遇到的代码字段含义]]></description><category></category></item><item><title><![CDATA[考虑特征提取和参数优化的锂离子电池健康状态统一估计框架]]></title><link>https://blog.youkuaiyun.com/qq_36623004/article/details/123661280</link><guid>https://blog.youkuaiyun.com/qq_36623004/article/details/123661280</guid><author>qq_36623004</author><pubDate>Tue, 22 Mar 2022 21:03:37 +0800</pubDate><description><![CDATA[A Uniform Estimation Framework for State of Health of Lithium-ion Batteries Considering Feature Extraction and Parameters Optimization

Absart

WTD

本研究提出了一个统一的估计框架，同时实现健康状态的估计和优化其中的健康特征，这些特征是基于固定范围内的充电电压曲线挖掘出来的。

Result and discussion

A、随机电压范围与优化电压范围的比较
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