gradient
简明释义
n. （尤指道路或铁路的）斜坡，坡度；（温度或压力变化的）梯度；（数学）斜率；梯度，梯度率；（数学）梯度算子
adj. 倾斜的；步行的，能步行的
复 数 g r a d i e n t s
英英释义
单词用法
气压梯度 | |
温度梯度 |
同义词
| 斜率 | 这座山的斜率很陡。 | ||
| 倾斜 | 道路的倾斜使得骑自行车很困难。 | ||
| 梯度 | 函数的梯度表示其变化率。 | ||
| 坡度 | 坡道的坡度对轮椅出入来说太高了。 | ||
| 上升 | 白天温度有显著上升。 |
反义词
| 平坦的 | 这条路很平坦，骑自行车很轻松。 | ||
| 水平的 | The surface of the table is level, ensuring that objects do not roll off. | 桌面的表面是水平的，确保物体不会滚落。 |
例句
1.Yes? How do I know the direction of a gradient?
我怎样知道梯度的方向？
为什么要说F是一个梯度场？
3.Zinnwaldite can be separated effectively by the high gradient magnetic separation from the tailing.
采用高梯度磁选可将铁锂云母从尾矿中有效分离。
4.Switch to the Gradient Tool (G).
切换到渐变工具(G)。
5.This one goes right away, by using the gradient factor.
方法是使用梯度因子，很快的得到了结果。
6.Yes, that's right. The gradient tool is evil.
好，我用渐变工具完成了水管、山、砖块。
7.It points opposite to the gradient.
指向和梯度向量相反。
8.So, the gradient is perpendicular.
所以，梯度向量是垂直的。
9.The hill has a steep gradient 坡度, making it difficult to climb without proper gear.
这座山的坡度 坡度很陡，使得没有适当装备很难攀爬。
10.The gradient 梯度 of the temperature change can be measured using a thermometer.
温度变化的梯度 梯度可以使用温度计来测量。
11.In calculus, we often calculate the gradient 梯度 of a function to find the direction of steepest ascent.
在微积分中，我们经常计算函数的梯度 梯度以找到最陡上升的方向。
12.In machine learning, adjusting the gradient 梯度 descent algorithm is crucial for minimizing error.
在机器学习中，调整梯度 梯度下降算法对最小化误差至关重要。
13.The color transition in the design has a smooth gradient 渐变 from blue to green.
设计中的颜色过渡有一个平滑的渐变 渐变，从蓝色到绿色。
作文
In mathematics and physics, the term gradient refers to a multi-variable generalization of the derivative. It is a vector that points in the direction of the greatest rate of increase of a function, and its magnitude represents the rate of change in that direction. Understanding the concept of gradient is crucial not only for mathematicians but also for engineers, scientists, and anyone involved in fields that require optimization or analysis of changes. For instance, in calculus, when we have a function describing a surface, the gradient can help us determine which way to move to ascend the steepest slope. To illustrate this, consider a hiker on a mountain. If the hiker wants to reach the peak as quickly as possible, they must identify the path that has the steepest incline. The gradient at any given point on the mountain indicates this steepest path. In this scenario, the hiker's understanding of the gradient can significantly affect their journey. Moreover, the concept of gradient extends beyond physical landscapes into various applications such as machine learning. In this field, algorithms often rely on the gradient to minimize error functions. By iteratively adjusting parameters in the direction indicated by the gradient, models can improve their predictions over time. This process is known as gradient descent, where the goal is to find the lowest point in a cost function, akin to finding the bottom of a valley. Additionally, in the realm of graphic design and computer graphics, gradient also has a different yet equally important meaning. Here, it refers to the smooth transition between colors. Designers use gradient effects to create depth and dimension in their visuals. A well-implemented gradient can enhance user experience by making interfaces more appealing and intuitive. Furthermore, the environmental sciences utilize the concept of gradient to understand phenomena like temperature changes and pollution levels across different terrains. For example, a temperature gradient can indicate how climate varies from one region to another, providing insights into weather patterns and ecological impacts. In summary, the term gradient is multifaceted, encompassing various meanings across different disciplines. Whether it is used to describe a mathematical concept, an optimization technique in machine learning, a design element, or a physical change in nature, understanding the gradient is essential for anyone looking to grasp complex systems or improve their problem-solving skills. Its applications are vast and varied, highlighting the importance of this concept in both theoretical and practical contexts. Therefore, mastering the idea of gradient can open doors to numerous opportunities in academic and professional fields alike.
在数学和物理学中，术语gradient指的是导数的多变量推广。它是一个指向函数最大增长率方向的向量，其大小表示该方向的变化速率。理解gradient的概念不仅对数学家至关重要，对于工程师、科学家以及任何涉及优化或变化分析的领域的人来说也是如此。例如，在微积分中，当我们有一个描述表面的函数时，gradient可以帮助我们确定朝哪个方向移动以攀登最陡的坡度。为了说明这一点，考虑一位在山上的徒步旅行者。如果这位徒步旅行者想尽快到达山顶，他们必须找出坡度最陡的路径。任何给定点上的gradient指示了这条最陡的路径。在这种情况下，徒步旅行者对gradient的理解可以显著影响他们的旅程。此外，gradient的概念超越了物理景观，扩展到机器学习等各种应用领域。在这个领域中，算法通常依赖于gradient来最小化误差函数。通过在gradient指示的方向上迭代调整参数，模型可以随着时间的推移改善其预测。这一过程被称为梯度下降（gradient descent），其目标是找到成本函数中的最低点，就像寻找一个山谷的底部一样。另外，在图形设计和计算机图形学的领域，gradient还有着不同但同样重要的含义。在这里，它指的是颜色之间的平滑过渡。设计师使用gradient效果来创造视觉上的深度和维度。一个良好实现的gradient可以通过使界面更具吸引力和直观性来增强用户体验。此外，环境科学利用gradient的概念来理解温度变化和不同地形的污染水平等现象。例如，温度gradient可以指示气候如何在一个地区与另一个地区之间变化，为天气模式和生态影响提供见解。总之，术语gradient是多方面的，涵盖了不同学科中的各种含义。无论它用于描述数学概念、机器学习中的优化技术、设计元素，还是自然中的物理变化，理解gradient对任何希望掌握复杂系统或提高问题解决能力的人来说都是至关重要的。它的应用广泛而多样，突显了这一概念在理论和实践背景下的重要性。因此，掌握gradient的思想可以为学术和专业领域开辟众多机会。
