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Applying Fuzzy Logic of Expert Knowledge for Accurate Predictive Algorithms of Customer Traffic Flows in Theme Parks
Abstract
This study analyzes two forecasting models based on the application of fuzzy logic and evaluates their effectiveness in predicting visitor expenditure and length of stay at a popular theme park. The forecasting models are based on a set of more than 600 decision rules constructed in the form of a complex series of IF-THEN statements. These algorithms store expert knowledge. A descriptive instrument that records the individual visitor's time spent and expenditure distribution on activities in the E-Da World in Taiwan was used to gather data. From a process of rigorous veriffication, the models developed are characterized by a high level of accuracy and efficiency.
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Authors (2)
-
Anestis Fotiadis
- I-Shou University - Tajwan
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- Publication version
- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.1142/S0219622016500425
- License
- Copyright (2016 World Scientific Publishing Company)
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- Category:
- Articles
- Type:
- artykuł w czasopiśmie wyróżnionym w JCR
- Published in:
-
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
no. 15,
edition 06,
pages 1451 - 1468,
ISSN: 0219-6220 - Language:
- English
- Publication year:
- 2016
- Bibliographic description:
- Korol T., Fotiadis A.: Applying Fuzzy Logic of Expert Knowledge for Accurate Predictive Algorithms of Customer Traffic Flows in Theme Parks// INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING. -Vol. 15, iss. 06 (2016), s.1451-1468
- DOI:
- Digital Object Identifier (open in new tab) 10.1142/s0219622016500425
- Verified by:
- Gdańsk University of Technology
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