The New Prediction Methodology for CO2 Emission to Ensure Energy Sustainability with the Hybrid Artificial Neural Network Approach

Energy is one of the most fundamental elements today’s economy. It becoming more important day by with technological developments. In order to plan energy policies countries and prevent climate change crisis, CO2 emissions must be under control. For this reason, estimation has become an factor for researchers scientists. study, a new hybrid method was developed using optimization methods. The Shuffled Frog-Leaping Algorithm (SFLA) algorithm recently preferred solving many problems. SFLA, swarm-based heuristic method, in study Levy flight method. Thus, speed reaching optimum result been improved. This which later, used structure Firefly (FA). next step, Artificial Neural Network (ANN)-based proposed estimate amount Türkiye. model had RMSE error 5.1107 R2 0.9904 testing dataset, respectively. last stage, Türkiye’s future emission examined three different scenarios. obtained results show that can successfully applied areas requiring estimation.