人工神经网络预测纯金属的表面张力

基金项目:

国家自然科学基金

详细信息

Estimating Surface Tension of Pure Metals by Neural Network

摘要: 建立了以纯金属原子半径、熔点、沸点和原子化焓预测表面张力的人工神经网络模型．训练后的神经网络能较好的拟会实验数据.对40种金属的表面张力进行回想和预测结果与实验值的偏差在可接受范围内，表明人工神经网络在纯金属表面张力预测方面有一定的前景．
- 表面张力 /
- 人工神经网络 /
- 反传学习
Abstract: An artificial neural network was established to forecast the surface tension of pure metal from the experimental data of atomic radius, melting point, boiling point and atomization enthalpies. The trained network can represent the relahonship between the input factors and output factor (surface tension).The associated and forecast data for more than 40 pure metals are acceptable considering the deviation of the experimental dara for surface tension, which shows a good prospect of artificial neural network in the prediction of surface tension of pure metals.
- surface tension /
- artificial neural network /
- back propagation learning