Clustering-Based Neural Network for Carbon Dioxide Estimation

被引：0

作者：

LI, Conghui ^{[1
]}

Zhong, Quanlin ^{[1
]}

LI, Baoyin ^{[1
]}

机构：

[1] Fujian Normal Univ, Coll Geog Sci, Fuzhou, Peoples R China

来源：

IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS | 2023年 / E106D卷 / 05期

基金：

中国国家自然科学基金;

关键词：

CO2 emission estimation; fuel consumption estimation; deep learning; clustering; intelligent transportation system; EMISSIONS;

D O I：

10.1587/transinf.2022DLL0012

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In recent years, the applications of deep learning have fa-cilitated the development of green intelligent transportation system (ITS), and carbon dioxide estimation has been one of important issues in green ITS. Furthermore, the carbon dioxide estimation could be modelled as the fuel consumption estimation. Therefore, a clustering-based neural network is proposed to analyze clusters in accordance with fuel consumption behav-iors and obtains the estimated fuel consumption and the estimated carbon dioxide. In experiments, the mean absolute percentage error (MAPE) of the proposed method is only 5.61%, and the performance of the proposed method is higher than other methods.

引用

页码：829 / 832

页数：4

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