- 算法優(yōu)化
- algorithm: n. 【數(shù)學(xué)】算法；規(guī)則系統(tǒng)；演段。
- optimization: n. 最佳化，最優(yōu)化。
- optimization algorithm: 最佳化算法; 最優(yōu)化算法
- boolean optimization algorithm: 布爾優(yōu)化算法
- global optimization algorithm: 全局優(yōu)化算法
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algorithm optimization中文什么意思
- 算法優(yōu)化
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例句與用法
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- Application of lmmunogenetic algorithm optimization in intersection signal timing
免疫遺傳算法在交叉口信號配時(shí)優(yōu)化中的應(yīng)用 - Genetic algorithm optimization based nonlinear ridge regression modeling method and its application in soft measurement
優(yōu)化的非線性嶺回歸方法及其在軟測量中的應(yīng)用 - This dissertation mainly focuses on the jpeg decoding algorithm optimization and its realization in the embed system , shows the core of software realization
文中主要就多處理器嵌入式系統(tǒng)環(huán)境下jpeg解碼算法的優(yōu)化和實(shí)現(xiàn)作為重點(diǎn),展示了軟件實(shí)現(xiàn)的核心。 - _ _ _ _ uncertain factors of macroscale inversion analysis of displacements are summed up . associated inversion model containing non - deterministic factors is proposed , i . e . " deterministic inversion of differential equation + systematic optimization technique = non - deterministic inversion " . the systematic optimization technique includes direct operator optimization , direct numerical analysis optimization , measurement design optimization , measured data processing , in - ersion algorithm optimization , and inverse operator regularization , etc . when this associated inversion technique is used in displacements back analysis , uncertain factors can be processed quantitatively
歸納了宏觀尺度位移反演分析的不確定性因素，提出了容納不確定性因素的位移反演分析的聯(lián)合反演模式，即“微分方程確定性反演+系統(tǒng)性優(yōu)化技術(shù)=非確定性反演”的模式，并具體論述了聯(lián)合反演模式的系統(tǒng)性優(yōu)化技術(shù)，包括正演算子的優(yōu)化、正演數(shù)值分析的優(yōu)化、測量設(shè)計(jì)優(yōu)化、觀測數(shù)據(jù)處理、反演算法優(yōu)化、反演算子處理等六個(gè)優(yōu)化方法。 - This algorithm easily escapes from local optimal solution , have high searching efficiency , simple structure , convenient use . aiming at iteration , optimization and matlab optimization toolbox having low precision and difficulty to choose initial vector on acquiring nonlinear equations ’ solutions , equations ’ solution problem is translated into genetic algorithm optimization problem . nonlinear equations ’ usual genetic
針對迭代法、最優(yōu)法、 matlab最優(yōu)化工具箱求解非線性方程組中存在求解精度不高及初始矢量難選等問題，將方程組求解問題轉(zhuǎn)化為遺傳算法函數(shù)優(yōu)化問題，建立了非線性方程組通用的遺傳算法解法，并將其用于汽車滑行試驗(yàn)數(shù)據(jù)處理中。