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- Smith-Waterman算法 Smith-Waterman algorithm
- 基于HPM模型的Smith-Waterman算法并行优化 Parallel Optimization of the Smith-Waterman Algorithm Based on HPM Model
- 实验结果表明,在基本不改变原Smith -Waterman算法的前提下,动态加速扣分策略顺利解决了序列局部联配中的马赛克问题,并且没有显著增加算法的复杂度(时间复杂度和空间复杂度)。 The method does not change the standard Smith Waterman algorithm much and the running time and space does not increase, while test results show the superior performance of the technique and potential for the sequence local alignment.
- 实验结果表明,自适应信息集成方法比用Smith Waterman和Jaro距离有更高的正确率。 The experimental results demonstrate that the self-adaptive approach for information integration achieves higher accuracy than that using Smith-Waterman edit distance and Jaro distance.
- 算法设计 algorithm design
- 算法设计与分析 The Design and Analysis of Algorithm
- 控制算法 control algorithm
- 聚类算法 clustering algorithm
- 启发式算法 heuristic algorithm
- 迭代算法 iterative algorithm
- 最优控制算法 algorithm for optimal control
- 渐缩算法 knapsack algorithm
- 调度算法 scheduling algorithm
- Ｋ－Ｐ算法 K-P calculation
- ＫＫＲ算法 KKR calculation
- 逼近算法 approximate algorithm
- "分裂和合并" 算法 split-and-merge algorithm
- 按序算法 sequential algorithm
- 编译算法 compiling algorithm
- 标准算法 canonical algorithm
