haku: @indexterm forecasting / yhteensä: 1417
viite: 12 / 1417
| Tekijä: | Hadavandi E. Ghanbari A. Shahanaghi K. |
| Otsikko: | Tourist arrival forecasting by evolutionary fuzzy systems |
| Lehti: | Tourism Management
2011 : OCT, VOL. 32:5 p. 1196-1203 |
| Asiasana: | tourism tourist industry forecasting |
| Vapaa asiasana: | tourist arrivals genetic fuzzy systems levene's test |
| Kieli: | eng |
| Tiivistelmä: | Accurate forecasts of tourist arrivals and study of the tourist arrival patterns are essential for the tourism-related industries to formulate efficient and effective strategies on maintaining and boosting tourism industry in a country. Forecasting accuracy is one of the most important factors involved in choosing a forecasting method. This paper presents a hybrid artificial intelligence (AI) model to develop a Mamdani-type fuzzy rule-based system to forecast tourist arrivals with high accuracy. The hybrid model uses genetic algorithm for learning rule base and tuning data base of fuzzy system. Results show that the proposed approach has high accuracy, so it can be considered as a suitable tool for tourism arrival forecasting problems. |
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