本文關(guān)鍵詞：支持向量機算法在化學(xué)化工中的應(yīng)用，由筆耕文化傳播整理發(fā)布。

探究支持向量機算法在化學(xué)化工中的應(yīng)用

Application of the Support Vector Machine Algorithm in Chemistry and Chemical Engineering

[1]

WANG Yan-fang .（Liaoning Chaoyang Radio and Television University, Liaoning Chaoyang 122000, China）

遼寧省朝陽廣播電視大學(xué),遼寧朝陽122000

文章摘要：計算機技術(shù)的快速發(fā)展，給化學(xué)化工數(shù)據(jù)的處理帶來極大便利。通過機器學(xué)習(xí)算法，Ⅱ丁以總結(jié)化學(xué)化工實驗規(guī)律，控制化工生產(chǎn)過程。原有的機器算法雖能為化學(xué)化工帶來很大便利，但是它本身就存在缺陷。機器學(xué)習(xí)算法的核心是數(shù)學(xué)中的漸近理論，這項理論的適用情景是必須有大量的樣本，而實際的化學(xué)化工作中樣本有限，這就可能導(dǎo)致計算中的過擬合。為了解決這一弊病，我們采用了向量機算法取代原有的機器算法，目前使用支持向量機算法（SVM）建立數(shù)學(xué)模型已經(jīng)得到國內(nèi)外的廣泛關(guān)注。筆者通過調(diào)查化學(xué)化工行業(yè)中SVM的使用情況，，闡述了向量機算法的優(yōu)勢，分析了它在食品檢驗、化工生產(chǎn)等多項領(lǐng)域的應(yīng)用。

Abstr：The rapid development of computer technology brings great convenience for processing of chemistry and chemical data. By machine learning algorithms, chemistry experiment law can be summarized to control chemical production process. Although the original machine algorithm can bring great convenience for the chemical industry, but it has defects itself. The core of machine learning algorithms is mathematical asymptotic theory, this theory is applicable to the scenario that must have a large number of samples, but the actual work samples in chemistry and chemical engineering are limited, which can lead to the over-fitting of calculation. To overcome this drawback, the support vector machine algorithm （SVM） has been used to replace the original machine algorithms; currently the support vector machine algorithm （SVM） has been widely used to establish mathematical models at home and abroad. In this paper, application of SVM in the chemical industry was introduced, advantages of SVM were described, and its anolication prosoect in various fields was analvzed.

文章關(guān)鍵詞：

Keyword：:Machine algorithm Overfitting Vector machine algorithm Chemistry

作者信息：會員可見

  本文關(guān)鍵詞：支持向量機算法在化學(xué)化工中的應(yīng)用，由筆耕文化傳播整理發(fā)布。