论文标题
使用多重优化器的非线性回归分析
Nonlinear Regression Analysis Using Multi-Verse Optimizer
论文作者
论文摘要
回归分析是一种重要的机器学习任务，用于在业务，体育分析等中进行预测分析。在回归分析中，优化算法在搜索回归模型中的系数中起着重要作用。在本文中，提出了使用最近开发的元元素多率优化器（MVO）的非线性回归分析。该提出的方法应用于10个众所周知的基准非线性回归问题。已经用粒子群优化器（PSO）进行了比较研究。实验结果表明，所提出的方法在统计上优于PSO算法。
Regression analysis is an important machine learning task used for predictive analytic in business, sports analysis, etc. In regression analysis, optimization algorithms play a significant role in search the coefficients in the regression model. In this paper, nonlinear regression analysis using a recently developed meta-heuristic Multi-Verse Optimizer (MVO) is proposed. The proposed method is applied to 10 well-known benchmark nonlinear regression problems. A comparative study has been conducted with Particle Swarm Optimizer (PSO). The experimental results demonstrate that the proposed method statistically outperforms PSO algorithm.
