四川环境2024，Vol.43Issue(3)：149-153,5.DOI:10.14034/j.cnki.schj.2024.03.023
基于非线性自回归神经网络模型对生活垃圾产生量的预测
Prediction of Domestic Waste Output Based on Nonlinear Autoregressive Neural Network Model
朱远超 1王晓燕 1田光1
作者信息
- 1. 北京市城市管理研究院,北京 100028||生活垃圾检测分析与评价北京市重点实验室,北京 100028
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摘要
Abstract
In this paper,a prediction model for the domestic waste output was established to better predict the domestic waste output,which can help building a plan for domestic waste disposal facilities and a flexible collection and transportation system.By using the non-linear auto-aggressive neutral network(NAR)and testing the model parameters such as delay order and the number of hidden layer neurons,a prediction model based on historical time series of domestic waste output was built.The results showed:The NAR neural network time series model had good predictability for the domestic waste output in Beijing.When the delay order was 5 and the number of hidden neurons was 10,the model achieved an r-value of 0.9717,a mean absolute percentage error of 3.385％,and a root mean square error of 5051.831 t/w.The residual sequence also passed the non-autocor-relation test,indicating a good prediction performance.The conclusion also indicated that NAR neural network model can be used for nonlinear autoregressive prediction of domestic waste output,without considering the availability of other related influencing factors,and had specific convenience and practical application significance.关键词
生活垃圾/预测模型/非线性自回归/神经网络Key words
Domestic waste/prediction model/nonlinear autoregression/neural network分类
资源环境引用本文复制引用
朱远超,王晓燕,田光..基于非线性自回归神经网络模型对生活垃圾产生量的预测[J].四川环境,2024,43(3):149-153,5.
