Το έργο με τίτλο Forecasting the success of a new tourism service by a neuro-fuzzy technique από τον/τους δημιουργό/ούς Atsalakis Georgios, Atsalaki Ioanna, Zopounidis Konstantinos διατίθεται με την άδεια Creative Commons Αναφορά Δημιουργού 4.0 Διεθνές
Βιβλιογραφική Αναφορά
G. S. Atsalakis, I. G. Atsalaki and C. Zopounidis, "Forecasting the success of a new tourism service by a neuro-fuzzy technique," Eur. J. Oper. Res., vol. 268, no. 2, pp. 716-727, Aug. 2018. doi: 10.1016/j.ejor.2018.01.044
https://doi.org/10.1016/j.ejor.2018.01.044
This paper presents a novel approach to forecasting the success of a newly launched service in tourism by using a hybrid intelligence system called the Adaptive Neuro Fuzzy Inference System (ANFIS). Recent studies have addressed the problem of modeling the success of a newly launched service by using different methods including artificial intelligence and model-based approaches. The ANFIS combines both the learning capabilities of a neural network and the reasoning capabilities of fuzzy logic to give enhanced forecasting capabilities, as compared to using a single methodology alone. Data collected through a questionnaire that concerns the variables of developing a new service in tourism have been used as inputs to the model. A new technique that is achieved by using a method that cycles through all the inputs and builds ANFIS models has been used for input reduction and input selection. The final model has been trained by leaving out a part of the data. The model was then evaluated by the data that were left out. The forecasting accuracy of the ANFIS model is evaluated by calculating well-known performance measures. The results have shown that ANFIS provides a prudent way to capture uncertainty in relationships among input variables and output variables to forecast the successful launch of a new tourism service. A comparative analysis with other methodologies confirms the superiority of the proposed approach.