F5知识点：学习曲线效应（The learning curve effect） 学习曲线效应指的是越是经常地执行一项任务，每次所需的时间就越少。 学习曲线将学习效果数量化绘制于坐标纸上，横轴代表练习次数（或产量），纵轴代表学习的效果（单位产品所耗时间），这样绘制出的一条曲线，就是学习曲线。 学习曲线有广义和狭义之分...
THE IMPORTANCE OF THE LEARNING CURVE EFFECT Learning curve models enable users to predict how long it will take to complete a future task. Management accountants must therefore be sure to take into account any learning rate when they are carrying out planning, control and decision-making. If the...
网络学习曲线效应 网络释义 1. 学习曲线效应 管理类术语 - TOMENY的BLOG -... ... 新手 rookie学习曲线效应learning-curve effect学习型组织 Learning Organization ... blog.csdn.net|基于8个网页 例句 释义: 全部,学习曲线效应
学习曲线（learning curves）与经验曲线（The experience curve）学习不是等比例前进的，而是一条曲线，由慢到快，由不熟练到熟练，由陌生到熟知，由伤脑筋到下意识，由起初的强制到后来的不用动脑筋的习惯养成。这也是学习过程的二八法则。简而言之，学习是一个加速过程，而不是一个匀速运动。开始可能三分耕耘一分...
网络经验曲线效应 网络释义 1. 经验曲线效应 经验曲线效应(learning-curveeffect)在电子工业非常出名,指的是越是经常地执行一项任务,每次所需的时间就越少。过去十 … guangfu.bjx.com.cn|基于2个网页
(BruceD.Henderson)首先提出了经验曲线效应(ExperienceCurveEffect)。 亨得森发现生产成本和总累计产量之间存有一致相关性。 如果一项生产任务被多次反复执行,它的生产成本将会随之降低。每一 次当产量倍增的时候,其代价(包括管理、营销、分销和制造费用等)将以一 ...
In this paper, we discuss what a learning curve effect is, the factors which effect it, how to display it, and how to incorporate the learning effect into the trial analysis. Bayesian hierarchical models are proposed to adjust the trial results for the existence of a learning curve effect. ...
learning curve n. 1.A graph that depicts rate of learning, especially a graph of progress in the mastery of a skill against the time required for such mastery. 2.The rate at which something can be learned or the degree of difficulty in learning something:a product with a difficult learning...
When surgeon experience with the MI-TLIF technique was considered in the cases of pseudarthrosis it was found that 93% of these cases occurred within the first two years of the study period, highlighting the effect that the MI-TLIF learning curve can have on patient outcomes. FDA Device/Drug...
(PCA); the variance of each successive PC decreases with a characteristic power law decay.cWhen learning with gradient descent, the weight matrix W learns each PC separately and in order of their variance. The sharpness of the sigmoidal learning curve is controlled by the network depth (SI ...