<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[绯荔榭•少年]]></title><description><![CDATA[苦，冲开后便淡]]></description><link>https://blog.youkuaiyun.com/HOMEGREAT</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; HOMEGREAT]]></copyright><item><title><![CDATA[浅谈大模型在新型电力系统建设中的应用前景]]></title><link>https://blog.youkuaiyun.com/HOMEGREAT/article/details/155158979</link><guid>https://blog.youkuaiyun.com/HOMEGREAT/article/details/155158979</guid><author>HOMEGREAT</author><pubDate>Sun, 23 Nov 2025 11:24:05 +0800</pubDate><description><![CDATA[大型语言模型在新型电力系统建设中展现出广阔应用前景，主要包括负荷与发电预测、智能调度优化、故障诊断、能源交易和用户交互等领域。通过处理高维非线性数据，大模型能提升预测精度和系统效率。然而，其应用仍面临数据隐私、计算资源、模型解释性和实时性等挑战。未来随着技术进步，大模型有望成为推动智能电网发展和实现&quot;双碳&quot;目标的关键技术，但需平衡创新与风险，加强跨领域合作和标准制定。]]></description><category></category></item><item><title><![CDATA[Python闯LeetCode--第3题：无重复字符的最长子串]]></title><link>https://blog.youkuaiyun.com/HOMEGREAT/article/details/139711113</link><guid>https://blog.youkuaiyun.com/HOMEGREAT/article/details/139711113</guid><author>HOMEGREAT</author><pubDate>Sat, 15 Jun 2024 23:59:10 +0800</pubDate><description><![CDATA[Python闯LeetCode--第3题：无重复字符的最长子串]]></description><category></category></item><item><title><![CDATA[python把一个整数列表转为字符串]]></title><link>https://blog.youkuaiyun.com/HOMEGREAT/article/details/139704866</link><guid>https://blog.youkuaiyun.com/HOMEGREAT/article/details/139704866</guid><author>HOMEGREAT</author><pubDate>Sat, 15 Jun 2024 16:53:15 +0800</pubDate><description><![CDATA[python把一个整数列表转为字符串]]></description><category></category></item><item><title><![CDATA[python将一个整数转为字符串列表]]></title><link>https://blog.youkuaiyun.com/HOMEGREAT/article/details/139704809</link><guid>https://blog.youkuaiyun.com/HOMEGREAT/article/details/139704809</guid><author>HOMEGREAT</author><pubDate>Sat, 15 Jun 2024 16:50:18 +0800</pubDate><description><![CDATA[python将一个整数转为字符串列表]]></description><category></category></item><item><title><![CDATA[Python闯LeetCode--第2题：两数相加]]></title><link>https://blog.youkuaiyun.com/HOMEGREAT/article/details/139704648</link><guid>https://blog.youkuaiyun.com/HOMEGREAT/article/details/139704648</guid><author>HOMEGREAT</author><pubDate>Sat, 15 Jun 2024 16:41:19 +0800</pubDate><description><![CDATA[Python闯LeetCode--第2题：两数相加]]></description><category></category></item><item><title><![CDATA[Python闯LeetCode--第1题：两数之和]]></title><link>https://blog.youkuaiyun.com/HOMEGREAT/article/details/139703696</link><guid>https://blog.youkuaiyun.com/HOMEGREAT/article/details/139703696</guid><author>HOMEGREAT</author><pubDate>Sat, 15 Jun 2024 15:55:35 +0800</pubDate><description><![CDATA[Python闯LeetCode--第1题：两数之和]]></description><category></category></item><item><title><![CDATA[程序员应该具备什么职业素养？]]></title><link>https://blog.youkuaiyun.com/HOMEGREAT/article/details/139667578</link><guid>https://blog.youkuaiyun.com/HOMEGREAT/article/details/139667578</guid><author>HOMEGREAT</author><pubDate>Fri, 14 Jun 2024 01:31:21 +0800</pubDate><description><![CDATA[编写高质量的代码是程序员的基本素养之一，包括良好的代码结构、清晰的注释、合理的命名规范等，能够编写易于理解、易于维护和易于扩展的代码。：在多人协作的项目中，团队合作是非常重要的，程序员需要具备良好的沟通能力和合作精神，能够与团队成员协作，共同完成项目。：作为一个优秀的程序员，需要不断改进自己的工作方法和流程，并进行反思和总结，不断提高自己的工作效率和质量。：在编写代码的过程中，程序员需要对自己的代码负责，并对代码的后续运行和维护负责，对自己的工作承担责任。]]></description><category></category></item><item><title><![CDATA[浅谈人工智能在新型电力系统建设和电力行业中的应用和未来发展趋势]]></title><link>https://blog.youkuaiyun.com/HOMEGREAT/article/details/139485308</link><guid>https://blog.youkuaiyun.com/HOMEGREAT/article/details/139485308</guid><author>HOMEGREAT</author><pubDate>Thu, 06 Jun 2024 00:40:59 +0800</pubDate><description><![CDATA[人工智能在新型电力系统建设和电力行业中具有广泛的应用和潜力，本文浅谈应用场景和未来发展趋势。]]></description><category></category></item><item><title><![CDATA[Python根据预设txt生成“你画我猜”题目PPT（素拓活动小工具）]]></title><link>https://blog.youkuaiyun.com/HOMEGREAT/article/details/138421963</link><guid>https://blog.youkuaiyun.com/HOMEGREAT/article/details/138421963</guid><author>HOMEGREAT</author><pubDate>Fri, 03 May 2024 18:57:29 +0800</pubDate><description><![CDATA[Python根据txt文件自动生成“你画我猜”题目PPT]]></description><category></category></item><item><title><![CDATA[Python中的深拷贝和浅拷贝]]></title><link>https://blog.youkuaiyun.com/HOMEGREAT/article/details/130614475</link><guid>https://blog.youkuaiyun.com/HOMEGREAT/article/details/130614475</guid><author>HOMEGREAT</author><pubDate>Thu, 11 May 2023 09:29:19 +0800</pubDate><description><![CDATA[浅析Python中深拷贝和浅拷贝的区别]]></description><category></category></item><item><title><![CDATA[Python实现离线音频转文字（时间分隔+区分说话人）]]></title><link>https://blog.youkuaiyun.com/HOMEGREAT/article/details/123980807</link><guid>https://blog.youkuaiyun.com/HOMEGREAT/article/details/123980807</guid><author>HOMEGREAT</author><pubDate>Thu, 07 Apr 2022 10:38:17 +0800</pubDate><description><![CDATA[免费领取并使用5小时讯飞开发平台时长后，运行Python代码完成离线音频转文字功能。]]></description><category></category></item><item><title><![CDATA[Win10下TexLive和TexMaker的安装]]></title><link>https://blog.youkuaiyun.com/HOMEGREAT/article/details/105888574</link><guid>https://blog.youkuaiyun.com/HOMEGREAT/article/details/105888574</guid><author>HOMEGREAT</author><pubDate>Sat, 02 May 2020 11:50:11 +0800</pubDate><description><![CDATA[Win10下TexLive和TexMaker的安装

文章目录Win10下TexLive和TexMaker的安装前言资源下载TexLiveTexMaker安装安装顺序TexLiveTexMaker验证参考资料
前言

Latex是一款常用的进行论文写作和排版的强大工具，在Windows系统下的常见使用配置是安装TexLive的latex环境，然后使用TexMaker或TexStudio等latex...]]></description><category></category></item><item><title><![CDATA[双线性插值]]></title><link>https://blog.youkuaiyun.com/HOMEGREAT/article/details/103401868</link><guid>https://blog.youkuaiyun.com/HOMEGREAT/article/details/103401868</guid><author>HOMEGREAT</author><pubDate>Thu, 05 Dec 2019 11:41:02 +0800</pubDate><description><![CDATA[双线性插值

文章目录双线性插值单线性插值双线性插值参考资料
单线性插值

已知数据 (x0, y0) 与 (x1, y1)，要计算 [x0, x1] 区间内某一位置 x 在直线上的y值（反过来也是一样，略）：
仔细看就是用x和x0，x1的距离作为一个权重，用于y0和y1的加权。双线性插值本质上就是在两个方向上做线性插值。

双线性插值

在数学上，双线性插值是有两个变量的插值函数的线性插值扩展，...]]></description><category></category></item><item><title><![CDATA[Numpy中矩阵乘法和点乘的区别]]></title><link>https://blog.youkuaiyun.com/HOMEGREAT/article/details/102916917</link><guid>https://blog.youkuaiyun.com/HOMEGREAT/article/details/102916917</guid><author>HOMEGREAT</author><pubDate>Tue, 05 Nov 2019 15:30:55 +0800</pubDate><description><![CDATA[Numpy中矩阵乘法和点乘的区别

import numpy as np

a = np.array([[1,2],
              [3,4]])
b = np.array([[5,6],
              [7,8]])

print('a*b:\n', a*b)  # element_wise 一一对应乘积
print('np.matmul:\n', np.matmul...]]></description><category></category></item><item><title><![CDATA[使用python的opencv将图像分割后的mask轮廓叠加在原图上]]></title><link>https://blog.youkuaiyun.com/HOMEGREAT/article/details/102689718</link><guid>https://blog.youkuaiyun.com/HOMEGREAT/article/details/102689718</guid><author>HOMEGREAT</author><pubDate>Tue, 22 Oct 2019 20:13:56 +0800</pubDate><description><![CDATA[使用python的opencv将图像分割后的mask轮廓叠加在原图上]]></description><category></category></item><item><title><![CDATA[浅谈Transformer]]></title><link>https://blog.youkuaiyun.com/HOMEGREAT/article/details/102504367</link><guid>https://blog.youkuaiyun.com/HOMEGREAT/article/details/102504367</guid><author>HOMEGREAT</author><pubDate>Fri, 11 Oct 2019 16:45:28 +0800</pubDate><description><![CDATA[《Attention Is All You Need》论文中Transformer模型的解读。]]></description><category></category></item><item><title><![CDATA[受限玻尔兹曼机（RBM）]]></title><link>https://blog.youkuaiyun.com/HOMEGREAT/article/details/100050950</link><guid>https://blog.youkuaiyun.com/HOMEGREAT/article/details/100050950</guid><author>HOMEGREAT</author><pubDate>Sat, 24 Aug 2019 11:39:41 +0800</pubDate><description><![CDATA[受限玻尔兹曼机（RBM）

文章目录受限玻尔兹曼机（RBM）概念详细讲解：
概念

Restricted Boltzmann machine（RBM），受限玻尔兹曼机。是一种无监督学习算法，是深度神经网络走红之前，常见的一种用于深度概率模型建模的模型。包含一层可观察变量（输入层）和一层潜在变量（隐藏层）。可以用下图表示：

上图中v为可见层，h为隐藏层，两层神经元一般都是二进制数。被叫做受限玻尔兹...]]></description><category></category></item><item><title><![CDATA[搜索评价指标 / 标签排序指标：nDCG]]></title><link>https://blog.youkuaiyun.com/HOMEGREAT/article/details/100037630</link><guid>https://blog.youkuaiyun.com/HOMEGREAT/article/details/100037630</guid><author>HOMEGREAT</author><pubDate>Fri, 23 Aug 2019 14:31:15 +0800</pubDate><description><![CDATA[nDCG, Normalized Discounted cumulative gain, 翻译为归一化折损累计增益。这个指标通常是用来衡量和评价搜索结果算法。]]></description><category></category></item><item><title><![CDATA[Tensorflow中因未释放计算图而导致显存爆炸运行越来越慢的问题]]></title><link>https://blog.youkuaiyun.com/HOMEGREAT/article/details/99687233</link><guid>https://blog.youkuaiyun.com/HOMEGREAT/article/details/99687233</guid><author>HOMEGREAT</author><pubDate>Fri, 16 Aug 2019 23:45:27 +0800</pubDate><description><![CDATA[Tensorflow中因未释放计算图而导致显存爆炸运行越来越慢的问题

问题描述

在一次模型修改中，因为需要在每运行一个batch时，调用另外一个模型计算相关的embedding导入进来当前模型，所以导致了会出现类似以下的调用方式：

    for batch in batches:
        with tf.Session() as sess:
            tfops = ...]]></description><category></category></item><item><title><![CDATA[Python计算一个文件夹下所有文件数量（包括子文件夹下的文件）]]></title><link>https://blog.youkuaiyun.com/HOMEGREAT/article/details/82861373</link><guid>https://blog.youkuaiyun.com/HOMEGREAT/article/details/82861373</guid><author>HOMEGREAT</author><pubDate>Thu, 27 Sep 2018 00:17:32 +0800</pubDate><description><![CDATA[Python计算一个文件夹下所有文件数量（包括子文件夹下的文件）

import os
def countFile(dir):
    tmp = 0
    for item in os.listdir(dir):
        if os.path.isfile(os.path.join(dir, item)):
            tmp += 1
        else:
    ...]]></description><category></category></item></channel></rss>