首页|基于WTD-PPAR的中国碳排放预测研究

基于WTD-PPAR的中国碳排放预测研究

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碳排放预测对我国的碳排放规划和政策颁布具有一定的参考价值.使用小波阈值去噪模型对碳排放数据建模能够有效缓解其存在的非线性和波动性问题,筛选得到数据的有效增长趋势.在此基础上,利用碳排放数据的时间序列特征建立其投影寻踪自回归(PPAR)模型,从而对碳排放进行预测分析.将该模型与未进行去噪的PPAR、BP、LSSVM、SVR、LSTM模型进行对比,发现WTD-PPAR模型的预测精度更高,预测结果更准确.分析结果显示,我国碳排放将在2029年达到峰值,约为1 081.89 mt,能够实现碳达峰的目标.
Research on Forecast of Carbon Emissions in China Based on WTD-PPAR Model
Carbon emission forecasting can play an effective role in promoting carbon emission planning and policy promulgation in our coun-try.The wavelet threshold denoising model can remove the noise in carbon emission data,and obtain the effective growth trend of the data.On this basis,the Projection Pursuit Autoregressive(PPAR)model is established by using the time series characteristics of carbon emission da-ta,so as to predict and analyze carbon emission.Compared with the PPAR model without denoising,BP,LSSVM,SVR and LSTM models,the WTD-PPAR model has higher prediction accuracy and more accurate prediction results.The results show that China's carbon emission will reach the peak in 2029,about 1 081.89mt,which can achieve the goal of carbon peak.

carbonemissionswavelet threshold denoisingprojection pursuitparasitic predator algorithmautoregression

楼泽瑶

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上海理工大学光电信息与计算机工程学院,上海 200082

碳排放 小波阈值去噪 投影寻踪 寄生捕食算法 自回归

2024

软件导刊
湖北省信息学会

软件导刊

影响因子:0.524
ISSN:1672-7800
年,卷(期):2024.23(2)
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