基于电子信息技术的工业物联网通信缺失数据预测方法

A method for Predicting Missing Data in Industrial Internet of Things Communication Based on Electronic Information Technology

工业物联网通过连接大量传感器和设备,实现工业生产的实时监控和优化。然而,由于复杂的通信环境和设备故障,数据缺失问题频发,对数据分析和智能决策构成挑战。基于电子信息技术的通信缺失数据预测方法,通过数据采集与预处理、特征提取、预测模型训练以及实时预测等环节,构建精确的预测模型,提升系统数据的完整性和连续性。文章探讨了该方法的实现过程和具体步骤,并通过实验验证其在实际应用中的有效性和优势。

The Industrial Internet of Things achieves real-time monitoring and optimization of industrial production by connecting a large number of sensors and devices.However,due to complex communication environments and equipment failures,data loss issues occur frequently,posing challenges to data analysis and intelligent decisionmaking.The communication missing data prediction method based on electronic information technology constructs an accurate prediction model through data collection,preprocessing,feature extraction,prediction model training,and real-time prediction,improving the integrity and continuity of system data.This article explores the implementation process and specific steps of the method,and verifies its effectiveness and advantages in practical applications through experiments.