Modeling CO_(2)Emission in Residential Sector of Three Countries in Southeast of Asia by Applying Intelligent Techniques

作     者：Mohsen Sharifpur Mohamed Salem Yonis M Buswig Habib Forootan Fard Jaroon Rungamornrat 

作者机构：Clean Energy Research GroupDepartment of Mechanical and Aeronautical EngineeringEngineering IIIUniversity of PretoriaPretoriaSouth Africa Department of Medical ResearchChina Medical University HospitalChina Medical UniversityTaichungTaiwanChina School of Electrical and Electronic EngineeringUniversiti Sains Malaysia(USM)Nibong Tebal14300PenangMalaysia Institute of Sustainable and Renewable Energy ISuREFaculty of EngineeringUniversityMalaysia Sarawak Department of Renewable EnergiesFaculty of New Sciences and TechnologiesUniversity of TehranTehranIran Center of Excellence in Applied Mechanics and StructuresDepartment of Civil EngineeringFaculty of EngineeringChulalongkorn UniversityBangkok10330Thailand 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2023年第74卷第3期

页      面：5679-5690页

核心收录：

学科分类：083002[工学-环境工程] 0830[工学-环境科学与工程（可授工学、理学、农学学位）] 07[理学] 08[工学] 0713[理学-生态学] 

基　　金：This work was funded by the Ministry of Higher Education Malaysia under the Fundamental Research Grant Scheme No.FRGS/1/2020/TK0/UNIMAS/03/4 

主　　题：CO_(2)emission GMDH MLP intelligent techniques energy consumption 

摘      要：Residential sector is one of the energy-consuming districts of countries that causes CO_(2)emission in large *** this regard,this sector must be considered in energy policy making related to the reduction of emission of CO_(2)and other greenhouse *** the present work,CO_(2)emission related to the residential sector of three countries,including Indonesia,Thailand,and Vietnam in Southeast Asia,are discussed and modeled by employing Group Method of Data Handling(GMDH)and Multilayer Perceptron(MLP)neural networks as powerful intelligent *** to modeling,data related to the energy consumption of these countries are represented,discussed,and ***,to propose a model,electricity,natural gas,coal,and oil products consumptions are applied as inputs,and CO_(2)emission is considered as the model’s *** obtained R^(2) values for the generated models based on MLP and GMDH are 0.9987 and 0.9985,***,values of the Average Absolute Relative Deviation(AARD)of the regressions using the mentioned techniques are around 4.56%and 5.53%,*** values reveal significant exactness of the models proposed in this article;however,making use of MLP with the optimal architecture would lead to higher accuracy.