The model of aircraft cost prediction based on least squares support vector machine with particle swarm optimizition

摘要

The prediction of aircraft cost plays a significant role in the construction of aircraft and equipment. This paper analyzes multiple factors that affect the aircraft cost according to the historical data of aircraft cost through principal component analyze (PCA), then builds the cost prediction model through the method of least squares support vector machine (LSSVM), and optimizes support vector machine's (SVM) parameters by means of particle swarm optimization (PSO) with the ability of fast convergence and better global search. The cost prediction model established as mentioned above has high precision and generalization ability.