一种基于AFSA的神经网络投影寻踪耦合回归模型

A AFSA-Based Coupling Regress Model of Neural Network Projection Pursuit

人工鱼群算法是通过模仿鱼群的觅食、聚群和追尾等行为寻找最佳觅食水域从而实现全局寻优的优化算法。应用神经网络的投影寻踪耦合回归模型存在优化问题,学习过程中运用人工鱼群算法进行优化,进而获得最佳的投影方向、阈值和正交Hermite多项式系数。本文描述了应用人工鱼群算法优化的神经网络投影寻踪耦合回归模型算法。仿真实验结果表明,该算法可以获得满意的预测效果。

Artifical Fish-swarm Algorithm is an optimization algorithm to achieve the global optimal result by imitates fish-swarm＇s behavior such as prey, swarm and follow. The optimization problem exists in applying neural networks to coupling the regress of projection pursuit, and using AFSA to optimize it in the learning process so as to attain the optimal projection direction, threshold and the Hermite orthogonal polynomial coefficients. The paper describes the AFS algorithm for coupling the regress model of neural networks and projection pursuit. The simulation results indicate that this algorithm gives a satisfactory forecast effect.