首页|基于GWO算法和NARX神经网络训练方法的高精度热电偶动态补偿模型构建与实践研究

基于GWO算法和NARX神经网络训练方法的高精度热电偶动态补偿模型构建与实践研究

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为提升热电偶测量精度和准确度,本文基于GWO算法和NARX神经网络训练方法,构建高精度的热电偶动态补偿模型,并进行实践研究.结果表明:该模型具有较高的精度和准确性,能有效预测和补偿热电偶的温度数据,对提高热电偶测量系统的性能和稳定性具有重要意义,可广泛用于工业自动化和环境监测等领域.
Construction and Practical Research of High-precision Thermocouple Dynamic Compensation Model Based on GWO Algorithm and NARX Neural Network Training Method
In order to improve the measurement precision and accuracy of thermocouple,this paper builds a high-precision thermocouple dynamic compensation model based on GWO algorithm and NARX neural network training method,and carries out practical research.The results show that the model has high precision and accuracy,and can effectively predict and compensate the temperature data of thermocouple,which is of great significance to improve the performance and stability of thermocouple measurement system,and can be widely used in industrial automation and environmental monitoring.

GWO algorithmNARX neural networkhigh precision thermocoupledynamic compensation model

张勇生

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佛山市质量计量监督检测中心

GWO算法 NARX神经网络 高精度热电偶 动态补偿模型

2024

计量与测试技术
成都市计量监督检定测试所

计量与测试技术

影响因子:0.175
ISSN:1004-6941
年,卷(期):2024.51(7)