This blog is the learning notes for preparing the preliminary exams of Queue theory, referring to Fundamentals of queueing theory

• Shortle, J. F., Thompson, J. M., Gross, D., & Harris, C. M. (2018). Fundamentals of queueing theory (Vol. 399). John Wiley & Sons.

1. Introduction

Queueing theory attempts to answer these questions through detailed mathematical analysis

There are many valuable applications of queueing theory including traffic flow(vehicles, aircraft, people, communications), scheduling (patients in hospitals, jobson machines, programs on a computer), and facility design (banks, post offices, amusement parks, fast-food restaurants).

This blog is the learning notes for preparing the preliminary exams of Queue theory, referring to Simulation modeling and analysis

• Law, A. M., Kelton, W. D., & Kelton, W. D. (2014). Simulation modeling and analysis (Vol. 3). New York: Mcgraw-hill.

1 Basic Simulation Modeling

Basic Simulation Modeling

1.1 The Nature of Simulation

Lectures:

• Simulation and modeling of natural processes | 自然过程的仿真与建模 | Python | ABM_哔哩哔哩_bilibili

This is a book about techniques for using computers to imitate, or simulate, the operations of various kinds of real-world facilities or processes.

analytic solution: 解析解

This blog is the learning notes for preparing the preliminary exams of Queue theory, referring to Introduction to operations research

• Hillier, F. S., & Lieberman, G. J. (2015). Introduction to operations research. McGraw-Hill.

1. Introduction

These kinds ofproblems and the need to find a better way to solve them provided the environment for theemergence of operations research (commonly referred to as OR)

Many of thestandard tools of OR, such as linear programming, dynamic programming, queueing theory,and inventory theory, were relatively well developed before the end of the 1950s

Three main characteristics of OR:

1. The research part of the name means that operations research uses an approach that resembles the way research is conducted in established scientific fields.
2. Still another characteristic of OR is its broad viewpoint.
3. An additional characteristic is that OR frequently attempts to search for a best solution (referred to as an optimal solution) for the model that represents the problem under consideration.

由于 MacBook 自身不具备合盖不休眠功能，而且在合盖的情况下就一定会进入休眠状态。休眠后网络将断开，下载任务也会停止。可以借助一串代码就可以完美的解决这个问题。

1. Python 解析和处理 xml 文件

1.1 SAX知识了解

SAX (simple API for XML) 有解析器和事件处理器：

• 解析器：负责读取XML文档，并向事件处理器发送事件，如元素开始跟元素结束事件。
• 事件处理器：则负责对事件作出响应，对传递的XML数据进行处理。

1. 引言

本篇博客是关于如何搭建 hexo 博客的完整教程，目的是为了帮助完全没有编程基础的小白能够成功的搭建一个自己的学习笔记博客网站。起因是因为个人有利用网站整理学习笔记的习惯，因此经常被问到如何搭建类似的网站，每次都苦恼于没有合适的文字资料分享给别人，这次跟几个小伙伴，打算出一期系统性的搭建各种常用的博客网站的教程，包括学习笔记博客和学术简历博客等，目前还在整理筹备中，尽情期待。

本篇博客主要为本人负责部分，基于 hexo ，从零开始搭建学习笔记博客网站，参考本人的博客： 独孤诗人的学习驿站。

10. 大模型之 Adaptation

使用语言模型（例如在上下文学习中）通过仅给出提示，我们已经能够执行一些任务。然而，提示方法并不适用于全部的下游任务，如自然语言推理 NLI、问题回答 QA、将网络表格转换为文本、解析电子健康记录 EHR 等。

9. 新的模型架构

通过前文的学习，我们知道神经预言模型的核心借口是一个将 token 序列映射到上下文嵌入的编码器：

$\text{the}, \text{mouse}, \text{ate}, \text{the}, \text{cheese}] \stackrel{\phi}{\Rightarrow} \left[\binom{1}{0.1}, \binom{0}{1}, \binom{1}{1}, \binom{1}{-0.1}, \binom{0}{-1} \right].$

7. 模型训练

上一章讨论了大语言模型 Transformer 的模型结构，本章节将讨论如何训练大语言模型，主要包含 目标函数 和 优化算法 两部分。

6. 模型架构

6.1 大模型之模型概括

语言模型可以被看做是一个黑箱，当前大规模语言模型的能力在于给定一个基于自身需求的prompt 就可以生成符合需求的结果。