首页|Product quality prediction based on RBF optimized by firefly algorithm

Product quality prediction based on RBF optimized by firefly algorithm

扫码查看
原文链接
  • NETL
  • NSTL
  • 万方数据
  • 维普
With the development of information technology,a large number of product quality data in the entire manufacturing process is accumulated,but it is not explored and used effec-tively.The traditional product quality prediction models have many disadvantages,such as high complexity and low accuracy.To overcome the above problems,we propose an optimized data equalization method to pre-process dataset and design a simple but effective product quality prediction model:radial basis function model optimized by the firefly algorithm with Levy flight mechanism(RBFFALM).First,the new data equalization method is introduced to pre-process the dataset,which reduces the dimension of the data,removes redundant features,and improves the data distribution.Then the RBFFALFM is used to predict product quality.Comprehensive expeūriments conducted on real-world product quality datasets validate that the new model RBFFALFM combining with the new data pre-processing method outperforms other previous meūthods on predicting pro-duct quality.

product quality predictiondata pre-processingradial basis functionswarm intelligence optimization algorithm

HAN Huihui、WANG Jian、CHEN Sen、YAN Manting

展开 >

College of Electronics and Information Engineering,Tongji University,Shanghai 201804,China

National Science and Technology Innovation 2030 Next-Generation Artifical Intelligence Major ProjectNational Natural Science Foundation of China

2018AAA010180172271188

2024

10.23919/JSEE.2023.000061

系统工程与电子技术(英文版)
中国航天科工防御技术研究院 中国宇航学会 中国系统工程学会 中国系统仿真学会

系统工程与电子技术(英文版)

CSTPCD
影响因子：0.64
ISSN：1004-4132
年,卷(期)：2024.35(1)
  • 40