例句與用法

1. This new algorithm speed up the image formation more significantly than the original one
   本文還分析了impsarwb - p這一特殊的成像算法的方位分辨率。
2. The algorithm speeds up network study train , compared with the real - time recurrent learning algorithm consumedly , and increases the accuracy of prediction
   與已有的實時循環(huán)學習算法相比，極大的提高了網(wǎng)絡(luò)學習訓練的速度，并且提高了預(yù)測的精度。
3. The migration algorithm proposed by this paper allow that the execution of process migrating and process going is concurring to the most degree . the migration algorithm speeds up the migration , reduces the communication overhead and avoids residual dependencies
   本文基于進程遷移的三個條件提出的進程遷移算法,最大程度地將進程狀態(tài)遷移和進程的運行并行起來,從而提高了遷移速度,網(wǎng)絡(luò)通信量也較小,而且也沒有對源節(jié)點的殘余依賴性。
4. In the post - process , uses the microsoft medias technical to design cartoon display mode , it raises cartoon speed and saves disc space , it can produce majority prevailing medias form . in interpolation , introduced dsi method , which improve the interpolation method of isoline , raise algorithm speed and efficiency , satisfy the real - time quality request . on the basis of scanning line algorithm , use opengl smooth interpolate method to improve the implementati
   在后處理過程中，引進了dsi插值方法，改進了以往等值線插值，提高了算法速度和效率，滿足了實時性要求，在掃描線算法的基礎(chǔ)上，引進了opm沁l插值方法，改進了云圖實現(xiàn)方法，提高了圖形顯示精度，在動畫格式上，我們可以根掘自己需要實現(xiàn)不同精度的不同壓縮格式動畫文件，提高了后處理顯示應(yīng)用場合，改變了以往動畫格式單一的形式。
5. Computing result shows that : coevolutionary mdo algorithms are effective on this problem ; distributed coevolutionary mdo algorithm is better than cooperate coevolutionary mdo algorithm ; asynchronous parallel version of distributed coevolutionary mdo algorithm speeds up the optimization procedure greatly while maintains good convergence performance ; multiobjective distributed coevolutionary mdo algorithm approximates the whole pareto optimal front well in only one single run , saves much computing cost than constraint method to obtain pareto optimal set , and greatly shortens search time by distributed asyn
   計算結(jié)果表明：協(xié)同進化mdo算法求解該問題是有效的，其中分布式協(xié)同進化mdo算法優(yōu)于合作協(xié)同進化mdo算法；異步并行的分布式協(xié)同進化mdo算法在保證收斂性能的同時大大加快了優(yōu)化進程；多目標的分布式協(xié)同進化mdo算法僅一次運行就很好的逼近了問題的整個pareto最優(yōu)前沿，比用約束法求解pareto最優(yōu)集節(jié)省了大量計算開銷，而且通過網(wǎng)絡(luò)多臺微機的分布式并行執(zhí)行大大縮短了搜索時間。