Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
11012134 | International Journal of Refrigeration | 2018 | 48 Pages |
Abstract
Performance and improvements of refrigeration systems are greatly related to the nucleate pool boiling heat transfer of refrigerant-oil mixtures containing nanoparticles (h). Empirical correlations have been used previously in order to estimate this parameter. Improved Adaptive Neuro-Fuzzy Inference System (ANFIS) is developed in this research applying different evolutionary algorithms to predict pool boiling heat transfer. To that end, 405 data samples were collected to construct the model and evaluate its performance based on each evolutionary algorithm. PSO-ANFIS model has the most accurate structure compared to other algorithms with R2=â¯0.998 and RMSEâ¯=â¯0.031 for all the 405 data samples. Moreover, the applicable domain of developed models was investigated and the dubious samples in the databank were indicated by using a technique based on Leverage algorithm.
Keywords
Related Topics
Physical Sciences and Engineering
Engineering
Mechanical Engineering
Authors
Ali Dehghan Saee, Alireza Baghban, Fariba Zarei, Zhang Zhien, Sajjad Habibzadeh,