Application of Regression Analysis Based on Genetic Particle Swarm Algorithm in Financial Analysis

摘要

Slow convergence speed and premature are two key problems existing in the regression analysis techniques based on genetic algorithm. To overcome the shortcomings, this paper proposes an improved regression analysis based on the genetic particle swarm algorithm. The basic principle is that a new operator is constructed to use PSO. This algorithm has the choice of genetic algorithms and genetic features, and drawing on the searching capabilities of particle towards the optimal forward. Finance analysis evaluates the efficiency of the algorithm. The experimental results show, the improved regression analysis is steady and greatly improve the convergent speed.