Improving the Quality of Production Management Processes Based on Neural Network and Neuro-Fuzzy Models and Tools

被引：0
|
作者：
Misnik, A. E. [1 ]
Shalukhova, M. A. [1 ]
机构：
[1] Belarusian Russian Univ, Mogilev 212000, BELARUS
来源：
PATTERN RECOGNITION AND IMAGE ANALYSIS | 2024年 / 34卷 / 03期
关键词：
neural network approach; fuzzy logic; defect recognition; neural network;
D O I：
10.1134/S1054661824700494
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
The article describes a way to improve the quality of product control processes in food production by means of neural network and neuro-fuzzy methods, models, and tools. It is proposed to use feature extraction using convolutional networks with further postprocessing in a fuzzy inference system. During the operation of the proposed system, a high percentage of correct recognitions was obtained (91.9%) and customer returns of products due to defects decreased by 63% compared to the same period last year. The results obtained show that defect identification using an adaptive neuro-fuzzy inference system is a suitable tool for solving defect analysis problems.
引用
收藏
页码：659 / 664
页数：6
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