石墨烯电热地板采暖的温度预测模型研究

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中图分类号：S776.01 文献标识码：A 文章编号：2095-2953（2025）08-0044-07

Research on Temperature Prediction Model for Graphene Electric Floor Heating

ZHANG Jia-wei， TANG Jia-cheng，SU Tian，LENG Xin，LIN Shu-yang， YU Pei-long， JIANG Tian，LI Ming-bao （Northeast ForestryUniversity，Harbin Heilongjiang15oO4O，China）

Abstract：At the pain points faced by forestry construction machinery incomplex working environments，such as insufficient durability，lowintellgencelevel，and poor ecological compatibility，this paper innovativelyproposes aninterdisciplinary integration technical path of graphene and forestry machinery.To address the problems oflarge inertia andlarge lag in the temperature control system of graphene electric heating flors，a temperature prediction model based on the Adaptive Neuro-Fuzzy Inference System （ANFIS） is proposed.A data acquisition device is developed to collect outdoor temperature，outdoor humidity，outdor wind speed，and indoor temperature，and an environmentalfactor dataset is established.The data is preprocessed using MATLAB software.After training and testing，an ANFIS temperature prediction model is established，and comparative studies arecaried out.The results show that the ANFIS temperature prediction model can fullyconsider complex temporal and spatial characteristics. Compared with the simple time-series data prediction model，the RNN prediction model，the average prediction eror of the ANFIS prediction model proposed in this paper is about 2.93% ，and it outperforms the comparative model in terms of convergence eficiency and prediction accuracy. Multiple experiments using data from working days and weekends furtherverifytheadaptabilityof this algorithm.Thispaper provides atheoreticalbasis intellgentupgradingofforestry equipment.

Key words：graphene electric heating floor；environmental factors；prediction model；ANFIS

随着林业工程机械化与智能化需求的不断提升，传统机械材料在极端作业环境下的性能瓶颈日益凸显。（剩余6667字）