Modeling CO2 Emission in Residential Sector of Three Countries in Southeast of Asia by Applying Intelligent Techniques

Residential sector is one of the energy-consuming districts countries that causes CO2 emission in large extent. In this regard, must be considered energy policy making related to reduction and other greenhouse gases. present work, residential three countries, including Indonesia, Thailand, Vietnam Southeast Asia, are discussed modeled by employing Group Method Data Handling (GMDH) Multilayer Perceptron (MLP) neural networks as powerful intelligent methods. Prior modeling, data consumption these represented, discussed, analyzed. Subsequently, propose a model, electricity, natural gas, coal, oil products consumptions applied inputs, model’s output. The obtained R2 values for generated models based on MLP GMDH 0.9987 0.9985, respectively. Furthermore, Average Absolute Relative Deviation (AARD) regressions using mentioned techniques around 4.56% 5.53%, These reveal significant exactness proposed article; however, use with optimal architecture would lead higher accuracy.