ESTIMATION OF ELAZIĞ TOURISM SATISFACTION ANALYSIS RESULTS USING WITH MULTILAYER PERCEPTRON (MLP) AND RADIAL BASIS FUNCTION (RBF) PREDICTION MODELS

Abstract

It is important for the sustainability of local, national, and international tourism activities when tourists leave satisfied with the places they have visited. A study was conducted on 400 local tourists in the autumn of 2021 in Elazığ. In the research, the satisfaction levels of domestic tourists regarding the services provided during their stay in the region were investigated. 

The aim of this study is the "Satisfaction" situation that emerged from the survey study; Estimating with MultiLayer Perceptron (MLP) and Radial Basis Function (RBF) models. In the study, while the error rate in the training phase of the MLP model was 7.7%, the error rate in the testing phase of the model was 7.8%. The error rate in the training phase of the RBF model was 18.8% and the error rate in the testing phase was 11.6%. In the training phase, the MLP model was 2.41 times more successful than the RBF model and in the testing phase, it was more successful 1.49 times than the RBF. Using the data obtained from the questionnaires, the architecture and various other parameters of both models were determined and the success of the models was compared. In the study, it was found that the MLP model gave better results compared to the RBF model.