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XCSR_DE1.0
- - XCS for Dynamic Environments + Continuous versions of XCS + Test problem: real multiplexer + Experiments: XCS is explored in dynamic environments with different magnitudes of change to the underlying concepts. +Reference papers: H.H.
lcs
- 动态规划实现lcs-Dynamic programming to achieve lcs
LCSp2264
- 动态规划的代码~LCS存路径DP：）状态压缩-Dynamic programming code path ~ LCS deposit DP:) compression status. .
LCS
- 用LCS方法解决字符匹配问题，用到动态规划的思想。原创-LCS solution with matching characters, the idea of using dynamic programming
lcs
- 一道经典的动态规划题目 浙江大学硕士生入学复试上机题 http://acm.hdu.edu.cn/showproblem.php?pid=1231-Classic dynamic programming http://acm.hdu.edu.cn/showproblem.php?pid=1231
LCS
- 算法动态规划最长公共子序列的递归实现，并包括查找过程的体现-Dynamic programming algorithm for the longest common subsequence of the recursive implementation, and includes the process to find a manifestation of
3
- 采用动态规划算法求最长公共串，LCS算法经典中的经典-A dynamic programming algorithm seeking longest common string
LCS
- LCS问题具有最优子结构和重叠子问题的性质，因此采用动态规划算法自底向上计算该问题的解，并输出求到的LCS。-LCS problem with sub-optimal substructure and overlapping nature of the problem, so a bottom-up dynamic programming algorithm for computing the solution of the problem, and the output request to
lcs
- 算法导论中最长公共子序列的实现，采用动态规划方法-Introduction to Algorithms in the realization of the longest common subsequence, dynamic programming method
LCS
- 利用动态规划算法寻找两个list中的最长公共子序列，并分别记录了最长公共子序列的在list中的结束位置-Dynamic programming algorithm to find the two list the longest common subsequence, and recorded the longest common subsequence of the end position in the list
3.1
- 最长公共子序列问题 最长公共子序列（动态规划） 实验数据：input.txt X={A,B,C,B,D,A,B} Y={B,D,C,A,B,A} ——要求给出X、Y的最长公共子序列Z，程序运行结束时，将计算结果输出到文件output.txt中。输出文件中包含问题的答案：找不到公共子序列时给出“null” 。 -Longest common subsequence problem LCS (dynamic programming) experimental data:
LCS
- LCS 动态归划解决char 类型的最长字符串的匹配问题-LCS program to solve dynamic return type char longest matching string
LCS
- VC实现输入两个字符串，利用动态规划思想求的最长公共子序列。有可视化界面。-VC the input two strings, the use of dynamic programming requirements of the longest common subsequence. A visual interface.
LCS
- 最长公共子序列的算法实现。基于动态规划的丝线实现的算法-The longest common subsequence algorithm. Realization of the algorithm based on dynamic programming thread
dongtaibianliang
- 动态规划中的lcs算法c++代码，可以作为lcs算法的参考代码 -Dynamic programming the lcs algorithm c++ code lcs algorithm can be used as a reference code
lcs
- 根据X和Y序列，利用动态规划计算出的所有LCS-The X and Y sequences is calculated using dynamic programming all LCS
Lcs
- 求最长公共子序列。本算法使用动态规划算法，解得最长公共子序列问题。-Find the longest common subsequence. The algorithm uses a dynamic programming algorithm, the solution was the longest common subsequence problem.
LCS
- 该程序用于求两个序列的最长子段，通过动态规划算法，记录子问题的结果，进而求出最终的最长子段。-The procedure used to find the longest sequence of two sub-sections, through dynamic programming algorithm to record the results of sub-problems, and then find the longest sub-section final.
lcs
- 用python实现了最长公共子序列LCS代码，分别应用递归方法和动态规划实现。并且实现了三个字符串的最长公共子序列。-Using Python to achieve the longest common subsequence of LCS code, respectively using recursive method and dynamic programming. And the realization of the longest common subsequence of three
源代码
- 大数据应用中基于支配点的mlcss算法设计与实现，程序中设计了三条字符串，查找他们之间的最长公共子序列。相对于传统的动态规划法，基于支配点思想具有更加高效的效率。(The design and implementation of mlcss algorithm based on dominant point in large data application, three strings are designed in the program to find the longest common