erf

简明释义

英[ɜːf]美[ɜːrf]

n. 小块土地

复 数 e r f s 或 e r v e n

英英释义

单词用法

同义词

反义词

例句

1.DFY the ERF technology to solve the problem?

丹凤眼erf技术能解决什么问题？

2.Ethylene response factor (ERF) proteins regulate a variety of stress responses in plant.

乙烯应答因子(ERF)参与调节植物许多逆境应答。

3.The studies have been did in the Shi Quan, Rice Center. Japan. The technical index such as material quality, energy consumption and drying efficiency erf drying facilities, have been analyzed.

本文介绍在日本国寺泉干燥中心测得的干湿谷混合干燥试验结果，分析混合干燥设施的能量消耗、干燥效率、物料品质等项技术指标。

4.It describes the relationship between electric field and resistance force of ERF shock absorber.

描述了新型电流变液体汽车减振器阻尼力与电场之间的关系。

5.Electrorheological fluid (ERF) is a kind of colloidal suspension whose apparent viscosity is variable in response to the strength of electric field.

电流变液是表观粘度随外加电场变化的一种胶质悬浮液。

6.On the basis of above mentioned efforts, the applications of ERF in machine equipment are studied.

在此基础上，研究了电流变体在机械装备中的应用。

7.The article demonstrates the mathematic model and damping characteristics of ERF dampener based on experiment, and presents some engineering idea for their structure.

在实验基础上论证了ERF减振器数学模型和阻尼特性，并给出结构设计思想。

8.Squeeze flow is one of the basic flow models of ERF.

挤压流是电流变液的基本流动模式之一。

9.Research on ERF chiefly concentrates at ERF damper in vibration domain at present. But still not go deep into to ERF shock isolator.

目前关于电流变流体（ERF）在振动领域的研究主要集中在ERF阻尼器，而对ERF隔振器的研究尚不很深入。

10.The scientist measured the erf to determine the diffusion of particles in the solution.

科学家测量了erf以确定溶液中颗粒的扩散。

11.In mathematics, the erf function is used to calculate probabilities in statistics.

在数学中，erf函数用于计算统计学中的概率。

12.Engineers often rely on the erf to model heat conduction in materials.

工程师们常常依赖erf来模拟材料中的热传导。

13.The erf is critical in understanding the behavior of random processes.

erf在理解随机过程的行为中至关重要。

14.Using the erf, we can predict the spread of contaminants in groundwater.

利用erf，我们可以预测污染物在地下水中的传播。

作文

In the realm of mathematics and engineering, the term erf plays a crucial role. The erf, or error function, is a special function that arises in probability, statistics, and partial differential equations. It is defined as the integral of the Gaussian distribution, which is fundamental in the field of statistics for calculating probabilities. Understanding the erf function is essential for anyone delving into these areas because it helps in determining how data behaves under a normal distribution. The error function is expressed mathematically as: erf(x) = (2/√π) ∫ from 0 to x e^(-t²) dt. This equation shows that the erf function essentially measures the probability that a random variable drawn from a normal distribution will fall within a certain range. For example, if we need to find the probability that a measurement falls between two values, the erf function can provide that information efficiently. In practical applications, the erf function is used in various fields such as physics, engineering, and finance. For instance, in heat transfer problems, the erf function can describe how heat diffuses through materials over time. Engineers often utilize this function to predict temperature changes in objects subjected to thermal energy. Similarly, in finance, the erf function can help in assessing risks and returns when dealing with assets that follow a normal distribution. Moreover, the erf function also has computational significance. Many algorithms in numerical analysis rely on the erf function for approximating integrals and solving differential equations. It is particularly useful in simulations that require statistical modeling. To illustrate the importance of the erf function, consider a simple example involving quality control in manufacturing. A factory produces light bulbs, and the lifetime of these bulbs follows a normal distribution. By using the erf function, quality control engineers can determine the proportion of bulbs that will last longer than a specific number of hours. This information is vital for ensuring product reliability and customer satisfaction. In conclusion, the erf function is not merely an abstract mathematical concept; it has real-world applications that affect various industries. Its ability to quantify probabilities and model behaviors in different contexts makes it an indispensable tool for professionals in mathematics, engineering, and beyond. Understanding the erf function allows individuals to make informed decisions based on statistical data, ultimately leading to better outcomes in their respective fields.

在数学和工程领域，术语erf起着至关重要的作用。erf或误差函数，是一个特殊函数，出现在概率、统计和偏微分方程中。它被定义为高斯分布的积分，这在统计学领域中是基础，用于计算概率。理解erf函数对任何深入这些领域的人来说都是必不可少的，因为它有助于确定数据在正态分布下的行为。 误差函数在数学上表示为： erf(x) = (2/√π) ∫ 从 0 到 x e^(-t²) dt。 这个方程表明，erf函数本质上测量从正态分布中抽取的随机变量落在某个范围内的概率。例如，如果我们需要找出某个测量值落在两个值之间的概率，erf函数可以有效地提供该信息。 在实际应用中，erf函数被广泛用于物理、工程和金融等多个领域。例如，在热传导问题中，erf函数可以描述热量如何随时间在材料中扩散。工程师通常利用该函数来预测受热能影响的物体的温度变化。同样，在金融领域，erf函数可以帮助评估在正常分布下处理资产时的风险和收益。 此外，erf函数在计算上也具有重要意义。许多数值分析中的算法依赖于erf函数来近似积分和解决微分方程。它在需要统计建模的模拟中尤其有用。 为了说明erf函数的重要性，考虑一个涉及制造质量控制的简单例子。一个工厂生产灯泡，而这些灯泡的寿命遵循正态分布。通过使用erf函数，质量控制工程师可以确定将持续超过特定小时数的灯泡比例。这些信息对于确保产品可靠性和客户满意度至关重要。 总之，erf函数不仅仅是一个抽象的数学概念；它具有影响各个行业的现实应用。它量化概率和在不同上下文中建模行为的能力，使其成为数学、工程及其他领域专业人士不可或缺的工具。理解erf函数使个人能够根据统计数据做出明智的决策，最终在各自领域取得更好的成果。