evolutionary algorithms的意思

evolutionary algorithms中文翻譯：

進化算法（preferencesetting的復數）

相似詞語短語

algorithms───n.[計][數]算法；算法式（algorithm的復數）

evolutionary───adj.進化的；發展的；漸進的

evolutionary biology───[醫]進化生物學；[生物]進化生物學

algorithms visualized───算法可視化

algorithms vazirani───vazard算法

evolutionary perspective───進化觀點

sorting algorithms───排序算法

algorithms definition───算法定義

evolutionary process───演化過程，進化過程；進化過程，演化過程

雙語使用場景

idea of evolutionary algorithms is not new.───進化式運算法則”并不是新的構想。

Genetic algorithms are a particular class of evolutionary algorithms.───遺傳算法是一類特殊的進化算法。

The computational time complexity is an important topic in the theory of evolutionary algorithms.───計算時間復雜性是演化理論中的一個重大課題。

ChatterBot - The aim of this project is to create a program which learns to use different languages by using evolutionary algorithms.───ChatterBot這個項目的目的是創建一個通過使用進化算法來學習使用不同語言的程序。

Genetic algorithm and ant colony algorithm are two evolutionary algorithms for complicated problems in combinatorial optimization.───大量實驗結果表明，這兩種算法在解決許多組合優化問題時都能表現出較好的求解能力。

Evolutionary Algorithms are adaptive algorithms about mocking evolutionary processes of life-form.───演化算法是一種模擬生物進化過程的自適應算法。

Soft computing includes Artifical Neural Networks, Fuzzy Logic, Evolutionary Algorithms, Rough Set (RS) Theory, etc.───軟計算工具主要包括人工神經網絡、模糊集理論、進化算法和粗糙集理論等。

In recent decades, multi-objective evolutionary algorithms became hot spots and achieved many good results in multi-objective area.───最近幾十年，演化算法成為多目標領域的研究熱點，并取得許多可喜的成績。

This paper studies evolutionary algorithms for single objective and multi-objective optimization.───本文對帶約束的單目標、多目標進化算法進行了研究。

英語使用場景

Adhibit efficiency function, The genetic annealing evolutionary algorithms are applied to realize the optimization of scheduling decisions.

Soft computing includes Artificial Neural Network, Fuzzy Logic, Evolutionary Algorithms, Rough Set ( RS ) Theory, etc.

The problem for time complexity of evolutionary algorithms ( EAs ) is rarely solved well before.

It proposed a unified fundamental structure of evolutionary algorithms and basic models.

The drawbacks of simulated evolutionary algorithms are that the global optimality can not be always guaranteed because of randomicity and premature con vergence.

Without requiring the differentiability of the functions and with implicit parallelism, evolutionary algorithms are often used to solve some difficult problems which the classical algorithms can't.

A general approach based on evolutionary algorithms to inverse parameter identification problems of PDEs is introduced.