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- Smith-Waterman算法Smith-Waterman algorithm
- 基于HPM模型的Smith-Waterman算法并行優(yōu)化Parallel Optimization of the Smith-Waterman Algorithm Based on HPM Model
- 實(shí)驗結果表明,在基本不改變原Smith -Waterman算法的前提下,動(dòng)態(tài)加速扣分策略順利解決了序列局部聯(lián)配中的馬賽克問(wèn)題,并且沒(méi)有顯著(zhù)增加算法的復雜度(時(shí)間復雜度和空間復雜度)。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.
- 實(shí)驗結果表明,自適應信息集成方法比用Smith Waterman和Jaro距離有更高的正確率。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.
- 算法設計algorithm design
- 算法設計與分析The Design and Analysis of Algorithm
- 控制算法control algorithm
- 聚類(lèi)算法clustering algorithm
- 啟發(fā)式算法heuristic algorithm
- 迭代算法iterative algorithm
- 最優(yōu)控制算法algorithm for optimal control
- 漸縮算法knapsack algorithm
- 調度算法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
- 編譯算法compiling algorithm
- 標準算法canonical algorithm