一种基于DeepSeek的生态环境机器学习方法的应用研究

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中图分类号：TP181；X830.2 文献标识码：A文章编号：2096-4706（2025）21-0039-05

Research on the Application of an Ecological Environment Machine Learning Method Based on DeepSeek

WAN Bin （Wuhan Ecologyand Environment Bureau Educationand Communication Center，Wuhan 43oo15，China）

Abstract： With the exponential growth of the scale andcomplexity ofenvironmental monitoring data，Machine Learming has become an effective means for processng environmental Big Data.However，theinterdisciplinarycognitive difference limits the in-depthapplicationofmachine learning methods inenvironmentalresearch.This study proposesa“DeepSeek + MachineLearning+environment”collaborativeparadigm.Taking thedataofthenational environmentalairqualityautomatic monitoring network in Wuhan in2023 asanexample，the DeepSeek platform isused tocomplete the whole process of data preprocessing，LSTM/XGBoostmodeling，trainingandhyperparameteroptimization.ThefialmodelRMSEis6.475and R2 is 0.871，which is 10.56% higher than the benchmark XGBoost.This result significantly reduces the technical threshold for noncomputer background researchers to apply Machine Learning.

Keywords：DeepSeek; Machine Learning; environmental Big Data; model optimization

0 引言

生态环境系统具有多物质耦合、多因素交互与多过程协同的典型特征，由此衍生的环境大数据通常呈现高维度属性。（剩余6843字）