摘要：In this study, Mamdani's and Sugeno's fuzzy inference systems (FIS) is presented for the concentration estimation of the Toluene gas by using the steady state sensor response. An artificial Neural Network (ANN) structure is also used for comparison. The Quartz Crystal Microbalance (QCM) type sensors were used as gas sensors. Acceptable performances were obtained for the concentration estimation with FISs and ANN. The results show that Sugeno's FIS performs better than Mamdani's FIS for gas concentration estimation. The estimation results of Sugeno's FIS are very closer to estimation results of ANN.
其他摘要：Bu çalışmada, Mamdani ve Sugeno bulanık sonuç çıkarım sistemleri (BSÇS) kararlı hal sensor cevapları kullanılarak Toluen gazının konsantrasyon tahmini için kullanılmış ve sunulmuştur. Bir yapay sinir ağı (YSA) yapısıda ayrıca mukayese için kullanılmıştır.
