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stochastic optimization in Chinese

Pronunciation:
How to pronounce "stochastic optimization""stochastic optimization" in a sentence

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  • 隨機規(guī)劃法

Examples

  • The stochastic optimization algorithm is studied and the model of the power management system is presented
    摘要研究了隨機最優(yōu)算法,并建立了該算法的電源管理系統(tǒng)模型。
  • Due to its character of " uphill climbing " , stochastic optimization algorithm is widely used to solve inverse problems
    因而具有“上山”性的隨機類優(yōu)化算法成為求解逆問題的主要數(shù)學(xué)工具。
  • Sa is a stochastic optimization technique that has been used to solve continuous , order discrete and muti - modal optimization problems
    模擬退火算法是一種用于解決連續(xù)、有序離散和多模態(tài)優(yōu)化問題的隨機優(yōu)化技術(shù)。
  • The stochastic optimization algorithm can get favorable equilibrium between the energy consumption and the reliability of performance in the system
    隨機最優(yōu)算法可以在節(jié)約系統(tǒng)能耗和保證系統(tǒng)性能之間取得較好的平衡。
  • The consumption - wealth ratio , the mean growth rate of economic and the portfolio shares were derived by using stochastic optimization method
    通過隨機最優(yōu)化方法,確定了均衡狀態(tài)下的消費財富比,期望經(jīng)濟增長率以及貨幣資本的份額。
  • He holds a phd in theoretical physics from the technical university of chemnitz , germany , where he investigated stochastic optimization algorithms on parallel computers
    他從德國chemnitz技術(shù)大學(xué)獲得理論物理博士學(xué)位,在大學(xué)里他研究了并行計算機上的隨即最優(yōu)化算法。
  • This paper mainly presents the method of solving inverse electromagnetic problems , the improvement of the stochastic optimization algorithm and the optimal designing of outer - rotor permanent motor
    本文討論了電磁場逆問題的求解方法,系統(tǒng)地進行了隨機類優(yōu)化算法的改進研究以及輪轂式永磁電機優(yōu)化設(shè)計的應(yīng)用研究。
  • The insurance company can also acquire various insurance products with stochastic interest by different combinations of parameters . establish a stochastic optimization model based on aggregate model of life insurance with stochastic interest
    保險公司通過參數(shù)的組合選擇,得到不同的隨機利率下的保險產(chǎn)品;同時,建立了隨機優(yōu)化模型。
  • Functions optimization for multi - modal functions optimization and non - stationary are one of important research subjects of function optimization . both of the problems are difficult to be solved by stochastic optimization algorithms in existence
    多模態(tài)函數(shù)和時變函數(shù)的隨機優(yōu)化問題是函數(shù)優(yōu)化的重要研究內(nèi)容,也是一個難以解決的問題。
  • Sa is a stochastic optimization technique and a zero - order algorithm requiring no derivative information and has been used extensively to solve continuous , ordered discrete and multi - modal optimization
    模擬退火法( kirkpatrick等, 1983 )是一種隨機的優(yōu)化技術(shù),它是零階算法,不需要導(dǎo)數(shù)信息,廣泛地用于解決連續(xù)的、有序離散及多模態(tài)優(yōu)化問題。
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