Abstract
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.
基金项目
National Science and Technology Innovation 2030 Next-Generation Artifical Intelligence Major Project(2018AAA0101801)
National Natural Science Foundation of China(72271188)
NETL
NSTL
维普
万方数据