数据结构栈和队列基本源代码，并包括银行模拟、中缀表达式计算、列车调度、农夫过河问题等经典数据结构算法。...

train reservation in visual basic

中缀表达式转换为后缀表达式并求值 使用switch语句-Infix expression into a suffix for the value of expression and the use of switch statement

Coursera课程关于大数据的任务。第一项任务。

迷宫的又一解法。该算法简单、实用、可读性强，是学习递归和回溯很好的例子。-maze of another solution. The algorithm is simple, practical and readable study is recursive and backtracking good example.

用vb写的饮食管理系统功能全面-with vb was eating a comprehensive management system function

IOI 2001 解题报告 内容：所有题目的详细分析以及参考程序 此外还有Ｔｅｓｔ数据-IOI 2001 Solving the contents of the report: a detailed analysis of all the topics and make reference to procedures in addition to Test Data

算法分析，算法理解，算法性能分析，算法综述等等。-Algorithm analysis, algorithm understanding, algorithm performance analysis, algorithm, etc..

完全由C语言实现的图的相关操作，就是清华大学 数据结构书里的图的所有算法的实现-Solely by the C language implementation of related plans to operate, that is, Tsinghua University, the data structure of the book" s map of the implementation of all algorithms

是我应我们学校学工部做的软件,其主要是解决想我们学校这样的条件--各个办公室之间还没有建立联网,而且学校分为两个校区（又不在一个城市). 　　因此，学工部每年的学分登记工作都很麻烦．每学年初，学工部要把当年发布的学分评测规定发到各系，学年末又要把从系里面提交的学分表收齐,然后手工登记,非常的麻烦.有时是系里面的学分报表太乱，有些资料丢失，要么是，系里面把各年的学分评测规定弄混，经常搞的他们一头雾水，于是为他们就请我做这个系统. 　　这个系统的工作流程是，每个学年初，学工部输入当年的学分评定规定，然后到处成为学分评测数据，然后Copy给各个系，各个系在每个学年中，输入新的专业，年级，班级和新生的资料，然后登记学分评测的纪录和考试的成绩．当学年末到了，各系把党学年的数据导成数据库，然后copy给学工部，学工部就可以用电脑纪录所有的学分纪录． -should I do our school among a software, it is our resolve to schools such conditions-- every office has not yet been established between the network and the school is divided into two campuses (not in a city). Therefore, each of the credit among a registration work very troublesome. Every beginning of the school year, among a year should release the credit evaluation of the provisions of the various faculties, should also learn from the end line inside the table collected credits, and then manual registration, very troublesome. Sometimes there is too much of the credit chaos statements, some of the inform

适合用来做K_Means 和K_NN的数据，一共150组，分成3个簇。-K_Means and make suitable for K_NN data, a total of 150 groups, divided into three clusters.