کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
63534 48222 2016 6 صفحه PDF سفارش دهید دانلود کنید
عنوان انگلیسی مقاله ISI
Prediction of GDP growth rate based on carbon dioxide (CO2) emissions
ترجمه فارسی عنوان
پیش بینی نرخ رشد تولید ناخالص داخلی بر اساس تولید گازهای گلخانه ای دی اکسید کربن (CO2)
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی کاتالیزور
چکیده انگلیسی


• In this investigation was analyzed the GDP prediction.
• Extreme Learning Machine (ELM) to predict GDP..
• ELM can be utilized effectively in applications of GDP emission forecasting.

The environment that governs the relationships between carbon dioxide (CO2) emissions and gross domestic product (GDP) changes over time due to variations in economic growth, regulatory policy and technology. The relationship between economic growth and carbon dioxide emissions is considered as one of the most important empirical relationships. However, rigorous economic causal analysis of the tradeoff between carbon dioxide (CO2) emissions and economic growth for credible climate change policies is still limited. The purpose of this research is to develop and apply the Extreme Learning Machine (ELM) to predict GDP based on CO2 emissions. The ELM results are compared with genetic programming (GP) and artificial neural network (ANN). The reliability of the computational models was accessed based on simulation results and using several statistical indicators. Coefficients of determination for ELM, ANN and GP methods were 0.9271, 0.8756 and 0.4475, respectively. Based upon simulation results, it is demonstrated that ELM can be utilized effectively in applications of GDP forecasting.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of CO2 Utilization - Volume 16, December 2016, Pages 212–217
نویسندگان
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