What is the translation of " 熵的概念 " in English?

• the concept of entropy

Examples of using 熵的概念 in Chinese and their translations into English

熵的概念应用到信道容量和热力学第二定律。
The concept of entropy applied to channel capacity and to the second law of thermodynamics.

熵的概念是由鲁道夫·克劳修斯在1865年引入。
The concept of entropy was introduced by Rudolf Clausius in 1865.

他还于1865年引进了熵的概念。
In 1865 he introduced the concept of entropy.

了解热力学第二定律的统计意义，熵的概念。
Understand the 2nd law of thermodynamics and the concept of entropy.

作者在附录中探讨了这个断言，其中引入了熵的概念。
(The writer explores this assertion in the Appendix where the concept of Entropy is introduced.).

直觉上这种分布（i）比其他的更“公平”，解释这个的一个方法是引用熵的概念。
One way to capture this intuition that distribution(i) is more"fair" than the other two is to invoke the concept of entropy.

例如，他们有几个人都运用了熵的概念，做出了非常重要的成果。
For instance, the notion of entropy was used by several of them with such important outcome.

这就是众所周知的熵的概念。
This is the well-known concept of entropy at work.

Clausius简单地概括了熵的概念：宇宙的能量是不变的。
Clausius summarized the concept of entropy in simple terms:“The energy of the universe is constant.

香农借用了热力学中熵的概念来描述信息的不确定性。
Shannon uses the concept of information entropy to describe the uncertainty of the source.

熵的概念最初是由克劳休斯（RudolphClausius）于1865年定义的。
The term"entropy" was first introduced by Rudolf Clausius in 1865.

重要性：它对于我们通过熵的概念来理解能量和宇宙是必不可少的。
Importance: Essential to our understanding of energy and the universe via the concept of entropy.

直到1948年，香农提出了“信息熵”的概念，才解决了对信息的量化度量问题。
In 1948, Shannon proposed the concept of information entropy to solve the problem of quantitative measurement of information.

这些问题的核心是熵的概念--这个词描述的是系统内粒子的混乱程度。
At the heart of these problems is the idea of entropy- a term which describes how disordered the particles in a system are.

正如物理学家在过去的几十年所认识到的那样，熵的概念与系统的信息含量是紧密相关的。
As physicists have realized over the past few decades, the concept of entropy is closely related to the information content of a system.

香农熵的基本概念就是所谓的一个事件背后的自信息（self-information），有时候也叫做不确定性。
The fundamental concept behind Shannon entropy is the so-called self-information of an event, sometimes called surprisal.

年，香农提出了”信息熵(entropy)“的概念.
Shannon CE(1948) A note on the concept of entropy.

热力学定律，其中涉及能源，焓，熵和自由能的概念，将被应用到化学系统。
The laws of thermodynamics, which involve energy, enthalpy, entropy and free energy concepts, will be applied to chemical systems.

所谓信息熵，是一个数学上颇为抽象的概念，在这里不妨把信息熵理解成某种特定信息的出现概率。
Information entropy, is a mathematically quite abstract concept, where the information entropy may wish to understand the probability of a particular information.

它的主要概念称为‘熵'，旨在测量随机变量的不确定性。
Its main concept, called entropy, aims to measure the uncertainty of random variables.

香农用信息熵的概念来描述信源的不确定度。
The concept of agricultural information entropy is used to describe the uncertainty of the source.

因此，信息熵是比热力学熵更广义的一个概念。
Therefore, information entropy is a broader concept than thermodynamic entropy.

非的熵概念”，皇家学会学报A469(2013).
The Entropy Concept for Non-Equilibrium States” Proceedings of the Royal Society A 469.

我们还可以将耗散与统计物理学中的熵概念联系起来。
We can also relate dissipation to the concept of entropy in statistical physics.

见埃利奥特·H·利布和雅各布恩加瓦松，“非平衡态的熵概念”，英国皇家学会学报A469(2013)：1-15。
See Elliott H. Lieb and Jakob Yngvason,“The Entropy Concept for Non-Equilibrium States,” Proceedings of the Royal Society A 469(2013): 1- 15.

十九世纪五十年代德国物理学家鲁道夫·克劳修斯通过引入他的熵概念，首次在数学上量化解释了热力学过程的不可逆性。
The German physicist Rudolf Clausius, in the 1850s, was the first to mathematically quantify the discovery of irreversibility in nature through his introduction of the concept of entropy.

你现在应该理解基本概念及熵，牛顿法的冷却，熵变化在日常生活中的例子。
You should now understand the basic concept of entropy, Newton's Law of Cooling, and examples of entropy changes in everyday life.

熵是一个来自物理学的概念，指的是某个系统中的“无序”的总量。
Entropy is a term from physics that refers to the amount of“disorder” in a system.

JohnPollard解释了力能学与熵这两个化学概念，是怎样统治了舞池的秩序。
John Pollard explains how two chemistry principles, energetics and entropy, rule the dance floor.

熵（entropy）概念香农指出，一条信息的信息量和它的不确定性之间有着直接的关系。
Shannon entropy indicates that the information volume of each piece of information is directly connected to its uncertainty degree.