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Development and evaluation of an adaptive neuro fuzzy interface models to predict performance of a solar dryer CIGR Journal
Bagheri, Nikrooz -.
 This research is carried out to predict energy efficiency of a solar dryer by adaptive neuro-fuzzy inference system (ANFIS) model. In this model, temperatures in the collector inlet, collector outlet and in the dry chamber exit and also absorbed heat energy by collector and necessary energy for evaporation of product moisture were considered as an ANFIS network inputs. To investigate the capability of ANFIS models in prediction of dryer efficiency, empirical model and regression analysis were used and their results were compared by ANFIS models. To evaluate an accuracy ANFIS models, statistical parameters such as mean absolute error, mean squared error, sum squared error, correlation coefficient (R) and probability (P) were calculated. Results indicated...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Agricultural machinery solar drying; Efficiency; ANFIS; Empirical modeling..
Ano: 2015 URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/2972
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