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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
