سال انتشار: ۱۳۹۰

محل انتشار: نوزدهمین کنفرانس مهندسی برق ایران

تعداد صفحات: ۶

نویسنده(ها):

Ramin Ayanzadeh – Young Researchers Club, Science and Research Branch, Islamic Azad University, Tehran
Azam S. Zavar Mousavi – Computer. Department, Science and Research Branch, Islamic Azad University, Tehran
Saeid Setayeshi – Nuclear Engineering Department, Amirkabir University of Technology, Tehran

چکیده:

Fossil fuels are precious limited sources of energy that are sorely vital for humanity, so it has always been emphasized and worldwide attention have widely focused on the issue. Excessive use of fossil fuels due to industrial developments in recent years has caused serious problems regarding ecology, environment and resource management, asfar as it made global challenges to control the consumption of fossil fuels. This research has accomplished to predict global fossil fuel consumption in coming decays. The records of data from global usage, indicates intrinsic chaotic behaviour of the data,therefore anticipation seems to be more difficult to implement it with conventional tools of time series prediction. In this paper anew approach is proposed as Amygdala-Orbitofrontal emotional learning model, to foresight the universal trend of fossil fuel consumption. Simulation results prove that theapplied method has prominent capability in forecasting chaotic time series. Thus, it can be claimed that the ultimate results is admissible for future works