基于GA-PSO算法的清酒质量等级研究

Study on the grade of wine quality based on GA- PSO algorithm

酒的质量等级评定是一件十分重要的工作。鉴于酒的质量等级为分类变量不能利用传统回归模型,于是采用Logistic回归模型进行建模。在结合一次对葡萄牙清酒全面调查所获得的实际数据的基础上,利用了有序Logistic回归构建了清酒质量等级预测模型,并利用了遗传算法(GA)、粒子群算法(PSO)、遗传-粒子群算法(GA-PSO)三种方法进行优化,得出GAPSO算法比上述其他两种算法能更有效地找出全局最优解。同时,找出了一组能获得最优质量等级的数据。

The wine quality grade evaluation is a very important work. Because the quality level of wine is a kind of classified variable,traditional regression model can＇t be unable to use,but the logistic regression model can. This paper uses order logistic regression to build a prediction model about wine quality grade which based on the actual data of a complete investigation of the Portuguese wine. Then it applies 3 kinds of algorithm,GA,PSO,GA- PSO,to find out that GA- PSO is better than the other two kinds and a group of factors which can get the best quality level.