TY - JOUR TT - Performance Estimation of Organic Rankine Cycle by Using Soft Computing Technics AU - Kovacı, Tuğba AU - Şencan Şahin, Arzu AU - Dikmen, Erkan AU - Şavklı, Hasan Burak PY - 2017 DA - October Y2 - 2017 DO - 10.24107/ijeas.297737 JF - International Journal of Engineering and Applied Sciences JO - IJEAS PB - Akdeniz University WT - DergiPark SN - 1309-0267 SP - 1 EP - 10 VL - 9 IS - 3 KW - Adaptive network fuzzy interference system KW - artificial neural networks system KW - Organic Rankine cycle KW - R365-mfc N2 - In this study, the thermal efficiencyvalues of Organic Rankine cycle system were estimated depending on thecondenser temperature and the evaporator temperatures values by adaptivenetwork fuzzy interference system (ANFIS) and artificial neural networks system(ANN). Organic Rankine cycle (ORC) fluids of R365-mfc and SES32 were chosen toevaluate as the system fluid. The performance values of ANN and ANFIS modelsare compared with actual values. 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