Characterisation of the plasma density with two artificial neural network models  

作　　者：王腾 高向东 李炜 

机构地区：[1]Faculty of Electromechanical Engineering,Guangdong University of Technology [2]School of Computer,South China Normal University [3]School of Physics and Telecommunication Engineering,South China Normal University

出　　处：《Chinese Physics B》2010年第7期91-95,共5页中国物理B（英文版）

基　　金：supported by the National Natural Science Foundation of China (Grant No. 60375012)

摘　　要：This paper establishes two artificial neural network models by using a multi layer perceptron algorithm and radial based function algorithm in order to predict the plasma density in a plasma system. In this model, the input layer is composed of five neurons： the radial position, the axial position, the gas pressure, the microwave power and the magnet coil current. The output layer is the target output neuron： the plasma density. The accuracy of prediction is tested with the experimental data obtained by the Langmuir probe. The effectiveness of two artificial neural network models are demonstrated, the results show good agreements with corresponding experimental data. The ability of the artificial neural network model to predict the plasma density accurately in an electron cyclotron resonance-plasma enhanced chemical vapour deposition system can be concluded, and the radial based function is more suitable than the multi layer perceptron in this work.This paper establishes two artificial neural network models by using a multi layer perceptron algorithm and radial based function algorithm in order to predict the plasma density in a plasma system. In this model, the input layer is composed of five neurons： the radial position, the axial position, the gas pressure, the microwave power and the magnet coil current. The output layer is the target output neuron： the plasma density. The accuracy of prediction is tested with the experimental data obtained by the Langmuir probe. The effectiveness of two artificial neural network models are demonstrated, the results show good agreements with corresponding experimental data. The ability of the artificial neural network model to predict the plasma density accurately in an electron cyclotron resonance-plasma enhanced chemical vapour deposition system can be concluded, and the radial based function is more suitable than the multi layer perceptron in this work.

关 键 词：plasma density PREDICTION multi layer perceptron radial based function 

分 类 号：O53[理学—等离子体物理]