parametrization

简明释义

英[pəˌræmətraɪˈzeɪʃən]美[pærəmetrɪˈzeɪʃən]

n. [数] 参数化；参数化法；[计] 参量化

英英释义

单词用法

同义词

反义词

例句

1.Parametrization programming of space intersection deep hole in casing machining of centrifugal compressor is set forth.

阐述了离心式压缩机机壳加工中的空间相交深孔的参数化编程方法。

2.The application is characterized by the parametrization design function and modularization design idea.

开发的应用程序实现了参数化设计和绘图，并贯穿了模块化设计思想。

3.For a certain application, some parametrization methods might behave better than the others.

对于某种应用。有些参数化方法要比其他的更好一些。

4.Parametrization design makes the design solution achieve the joining of data and graph.

采用参数化设计的方法使设计结果实现了数据与图形的结合。

5.Have you ever practised customizing (parametrization) at least in SAP?

曾经有你熟练的在笨蛋至少定制（参数化）?。

6.Parameterization (also, parametrization/parameterisation/parametrisation) is the process of deciding and defining the parameters necessary for a complete or relevant specification

参数化（Parameterization）（通常也用parametrization/parameterisation/parametrisation）是为一个完整的或者相关的规格确定或定义必要参数的流程。

7.Understanding parametrization can significantly improve the accuracy of simulations in physics.

理解参数化可以显著提高物理模拟的准确性。

8.The software allows users to create custom functions through parametrization of input variables.

该软件允许用户通过输入变量的参数化创建自定义函数。

9.In computer graphics, parametrization is essential for modeling surfaces and textures effectively.

在计算机图形学中，参数化对于有效建模表面和纹理至关重要。

10.The engineer used parametrization to optimize the design of the mechanical component.

工程师使用参数化来优化机械部件的设计。

11.The mathematician discussed the concept of parametrization in relation to curves, explaining how it allows for a more flexible representation.

数学家讨论了与曲线相关的参数化概念，解释了它如何允许更灵活的表示。

作文

In the realm of mathematics and engineering, the concept of parametrization is fundamental. It refers to the process of defining a set of parameters that can describe a curve, surface, or any geometric object in a more manageable way. By using parametrization techniques, complex shapes can be represented through simpler equations, making them easier to analyze and understand. For instance, consider the circle: instead of using the traditional equation x² + y² = r², we can employ parametrization by expressing the coordinates in terms of a single variable, typically an angle θ. In this case, we can define the circle with the equations x = r * cos(θ) and y = r * sin(θ), where θ varies from 0 to 2π. This transformation not only simplifies calculations but also provides deeper insights into the geometry of the shape.The significance of parametrization extends beyond pure mathematics; it plays a crucial role in various fields such as physics, computer graphics, and robotics. For example, in computer graphics, parametrization allows for the creation of textures on 3D models. When creating a 3D object, artists often need to map a 2D image onto the surface of the model. This process involves defining parameters that relate the 2D texture coordinates to the 3D surface points. Without effective parametrization, the textures could appear distorted or misaligned, leading to unrealistic representations.Moreover, in the field of robotics, parametrization is essential for motion planning and control. Robots often need to navigate through complex environments, and parametrization helps in defining the paths they should take. By using parameters to represent the robot's position and orientation, engineers can develop algorithms that optimize movement while avoiding obstacles. This application of parametrization not only enhances efficiency but also ensures safety in robotic operations.Another area where parametrization proves invaluable is in data analysis and machine learning. In these domains, we often deal with high-dimensional data. To simplify the analysis, we can use parametrization techniques such as dimensionality reduction. Methods like Principal Component Analysis (PCA) involve transforming the original variables into a new set of parameters that capture the most variance in the data. This allows researchers to visualize and interpret complex datasets more effectively, leading to better-informed decisions.In summary, parametrization is a powerful tool that transcends mathematical theory and finds applications in various practical fields. It simplifies complex problems by reducing them to manageable parameters, facilitating analysis and understanding. Whether in mathematics, computer graphics, robotics, or data science, the ability to effectively utilize parametrization can significantly enhance our capabilities and lead to innovative solutions. As we continue to explore and expand our knowledge in these areas, mastering the concept of parametrization will undoubtedly remain a key skill for future advancements.

在数学和工程领域，参数化的概念是基础性的。它指的是定义一组参数的过程，这些参数可以以更可管理的方式描述曲线、表面或任何几何对象。通过使用参数化技术，复杂的形状可以通过更简单的方程表示，从而使其更易于分析和理解。例如，考虑圆：我们可以不使用传统的方程x² + y² = r²，而是通过将坐标用单个变量（通常是角度θ）来表达，采用参数化。在这种情况下，我们可以用方程x = r * cos(θ)和y = r * sin(θ)来定义圆，其中θ从0变化到2π。这种变换不仅简化了计算，还提供了对形状几何的更深刻理解。参数化的重要性超越了纯数学；它在物理学、计算机图形学和机器人等各个领域中发挥着至关重要的作用。例如，在计算机图形学中，参数化允许在3D模型上创建纹理。当创建3D对象时，艺术家通常需要将2D图像映射到模型的表面。这个过程涉及定义将2D纹理坐标与3D表面点关联的参数。如果没有有效的参数化，纹理可能会出现失真或错位，导致不现实的表现。此外，在机器人领域，参数化对于运动规划和控制至关重要。机器人通常需要在复杂的环境中导航，而参数化有助于定义它们应采取的路径。通过使用参数来表示机器人的位置和方向，工程师可以开发优化运动的算法，同时避免障碍物。这个参数化的应用不仅提高了效率，而且确保了机器人操作的安全性。参数化证明在数据分析和机器学习中也极为宝贵。在这些领域，我们经常处理高维数据。为了简化分析，我们可以使用像降维这样的参数化技术。主成分分析（PCA）等方法涉及将原始变量转换为一组新的参数，这些参数捕捉数据中的最大方差。这使研究人员能够更有效地可视化和解释复杂数据集，从而做出更明智的决策。总之，参数化是一个强大的工具，它超越了数学理论，并在各种实际领域中找到了应用。它通过将复杂问题简化为可管理的参数，促进了分析和理解。无论是在数学、计算机图形学、机器人还是数据科学中，有效利用参数化的能力都能显著增强我们的能力，并带来创新的解决方案。随着我们继续探索和扩展这些领域的知识，掌握参数化的概念无疑将成为未来进步的关键技能。