مشخصات پژوهش

عنوان	Estimation of Isentropic Compressibility of Biodiesel Using ELM Strategy: Application in Biofuel Production Processes
نوع پژوهش	مقاله چاپ‌شده در مجلات علمی
کلیدواژه‌ها	Extreme learning machine, Isentropic compressibility, Machine learning, Biodiesel, Sensitivity analysis
چکیده	Isentropic compressibility is one of the significant properties of biofuel. On the other hand, the complexity related to theexperimental procedure makes the detection process of this parameter time-consuming and hard. Thus, we propose a newMachine Learning (ML) method based on Extreme Learning Machine (ELM) to model this important value. A real databasecontaining 483 actual datasets is compared with the outputs predicted by the ELM model. The results of this comparison showthat this ML method, with a mean relative error of 0.19 andR2values of 1, has a great performance in calculations related to thebiodieselfield. In addition, sensitivity analysis exhibits that the most efficient parameter of input variables is the normal meltingpoint to determine isentropic compressibility.
پژوهشگران	سید مهدی علیزاده (نفر پنجم)، اددوین ایسولا لاوال (نفر چهارم)، تزو چیا چن (نفر سوم)، میثم حسینی (نفر دوم)، ماریسچا الونی (نفر اول)