针对液体推进剂A现有分析方法的不足 ,利用神经网络法自学习、自适应、自组织等特性以及其高度的非线性表达能力 ,模拟酸碱滴定过程的实质 ,提出了一种基于神经网络的电位滴定方法 ,可以实现对液体推进剂A中的多组分物质一次性快速准确测定。结果表明 ,该方法准确可靠。 Aiming at the deficiency of the existing analysis methods of Liquid Propellants A, the neural network method is used to simulate the essence of acid-base titration process by using the characteristics of self-learning, self-adaptation and self-organization of neural network and its highly nonlinear expression ability. Potentiometric titration method can be achieved for liquid propellant A multi-component substances in a one-time rapid and accurate determination. The results show that the method is accurate and reliable.