马尔可夫过程英文解释翻译、马尔可夫过程的近义词、反义词、例句
英语翻译：
【计】 markov process
分词翻译：
马的英语翻译：
equine; gee; horse; horseflesh; neddy; steed
【医】 hippo-
尔的英语翻译：
like so; you
可的英语翻译：
approve; but; can; may; need; yet
夫的英语翻译：
goodman; husband; sister-in-law
过程的英语翻译：
course; procedure; process
【计】 PROC
【化】 process
【医】 course; process
【经】 process
网络扩展解释
马尔可夫过程 (Mǎ ěr kě fū Guò chéng)
马尔可夫过程，又称马尔科夫过程、马尔可夫链，是一种数学模型，用于描述在经过一系列有确定条件的状态转移后，某个系统从一个状态变为另一个状态的随机过程。这种转移的概率只依赖于当前状态，而与之前的状态无关，因此也被称为“无记忆性过程”。
Markov process
A Markov process, also known as a Markov chain, is a mathematical model used to describe a random process where a system transitions from one state to another state after a series of predetermined conditions have been met. The probability of these transitions only depends on the current state and is independent of previous states. Therefore, it is also known as a "memoryless process".
Pronunciation
马尔可夫过程：mǎ ěr kě fū guò chéng (má ěr kě fū guò chéng)
Markov process：ˈmär-kəf prä-ˌses
Usage
马尔可夫过程在数学、自然语言处理、经济学、物理学、生命科学等领域有着广泛的应用。它可以用来模拟随机系统的动态过程，例如股票价格的变化、天气的转移、自然语言中的语义分析等。
The Markov process has a wide range of applications in various fields such as mathematics, natural language processing, economics, physics, life sciences, etc. It can be used to model dynamic processes in random systems, such as changes in stock prices, weather transitions, semantic analysis in natural language, etc.
Example Sentence
马尔可夫过程是将系统的未来状态描述为概率分布的数学方法。
The Markov process is a mathematical method for describing the probability distribution of a system's future state.
Synonyms
马尔可夫链 (Mǎ ěr kě fū liàn)：Markov chain
Antonyms
确定性过程 (què dìng xìng guò chéng)：Deterministic process
Word Frequency
根据 Google Books Ngram Viewer 的数据，在英文书籍中，“Markov process”在20世纪中期开始流行，使用频率逐渐增加，并在21世纪达到高峰。
According to the data from Google Books Ngram Viewer, "Markov process" became popular in English books in the mid-20th century, and its usage frequency gradually increased, reaching its peak in the 21st century.