عنوان	Applying Conventional and Intelligent Approaches to Model the Minimum Spouting Velocity of Vegetable Biomasses in Conical Spouted Beds
نوع پژوهش	مقاله چاپ‌شده در مجلات علمی
کلیدواژه‌ها	Conical spouted beds,Minimum spouting velocity,Vegetable biomasses,Intelligent models,Correlation
چکیده	This study aimed to model the minimum spouting velocity (U_ms) of vegetable biomasses in conical spouted beds including five biomasses. A statistical analysis of the literature correlations corroborated the lack of accurate models, since the average absolute relative errors (AAREs) exceeding 26%. Therefore, a new simple correlation was developed based on reliable data and the least square fitting method (LSFM) that improves the predictions for U_ms. Furthermore, three predictive methods were also designed based on intelligent approaches. The model developed based on the Gaussian Process Regression (GPR) provides the most accurate results with excellent AARE and R^2 values of 5.42% and 97.02%, respectively, in the testing step. The novel models were found to be applicable for vegetable biomasses of different shapes, as they excellently described the trends of U_ms under different conditions. Finally, the parameters of greatest influences on the performance of the models were discovered through a sensitivity analysis.
پژوهشگران	محمد امین مرادخانی (نفر اول)، سید حسین حسینی (نفر دوم)، مجتبی کرمی (نفر سوم)، مارتین الازار (نفر چهارم)، جان سالداریگا (نفر پنجم)