particle swarm的意思

particle swarm中文翻譯：

顆粒群

相似詞語短語

swarm───v.成群來回移動；蜂擁而至；擠滿；爬；（蜜蜂）成群飛離蜂巢；n.一大群；蜂群；人群；一大群小型天體同時在空中出現

particle───n.顆粒；[物]質點；極小量；小品詞

god particle───上帝粒子

swarm app───swarm應用程序

feel swarm───感覺蜂群

swarm with───擠滿，充滿；充滿；擠滿

particle beam───粒子束，[高能]粒子束流

particle crossword───粒子縱橫字謎

microbe swarm───微生物群

雙語使用場景

Particle swarm Optimization (PSO) algorithm is based on swarm intelligence theory.───粒子群優化(PSO)算法是基于群體智能理論的優化算法。

Particle swarm algorithm was an optimized algorithm based on swarm intelligence.───粒子群算法是一類基于群智能的隨機優化算法。

In this paper, we review ant colony algorithm and particle swarm optimization.───本文討論了群集智能的兩種算法，蟻群智能與微粒群智能。

Particle swarm optimization is an extremely simple algorithm that seems to be effective for optimizing a wide range of functions.───粒子群優化是一個非常簡單的算法，似乎是有效的優化了廣泛的職能。

It used to solve the problem that Particle Swarm Optimization(PSO) easily falls into a local extremum.───克服了經典粒子群算法中參數選擇問題以及粒子群算法易陷入局部極值問題。

Task assignment problem is a typical NP problem. Particle Swarm Optimization (PSO) algorithm was used to solve task assignment problem.───任務指派問題是典型NP難題，引入粒子群優化算法對其進行求解。

Theory analysis of particle swarm optimization is always an important research topic.───微粒群算法的理論分析一直是其研究的難點。

Classification is one tasks of data mining, using particle swarm optimization in classification especially classification rule extraction.───分類是數據挖掘研究的主要內容之一，將微粒群算法應用于分類問題，進行分類規則的提取。

To this problem, this paper proposed one kind of method to choose the parameters of the SVM by particle swarm optimization algorithm (PSO).───針對此問題，提出一種基于粒子群優化算法的支持向量機參數選擇方法。

英語使用場景

The results have shown the effectiveness of particle swarm optimization for flexible job shop scheduling.

A modified particle swarm optimization algorithm for nonlinear system identification is presented.

For locating the critical failure surface, the particle swarm or the harmony method is used, which is an upper bound approach.

Particle swarm optimized particle filter (PSOPF) incorporates the newest observations into sampling process and also optimizes it.

A cultural-based particle swarm optimization (CBPSO) algorithm is proposed to improve the computational accuracy and efficiency of PSO and avoid premature.

An improved immune particle swarm optimization was presented in this study in order to increase the effectiveness of feature selection for emotion recognition based on Galvanic Skin Response (GSR).

Compared with the real data, particle swarm neural network with sliding time window technique in modeling the mid and long term electric load is effective, and the model can meet the actual demands.

A new improved discrete particle swarm optimization algorithm is designed to tackle the Traveling Salesman Problem.

An algorithm for discretization based on Particle swarm optimization (PSO) is presented, which can settle the problem of continuous attributes discretization in systema modeling perfectly. ?