CAPACITY ANALYSIS OF CHECK-IN UNITS IN AIRPORTS USING FUZZY LOGIC AND ARTIFICIAL NEURAL NETWORK APPROACHES
| dc.contributor.author | Kiyildi, Recep Koray | |
| dc.contributor.editor | Larauge, PB | |
| dc.contributor.editor | Castille, ME | |
| dc.date.accessioned | 2019-08-01T13:38:39Z | |
| dc.date.available | 2019-08-01T13:38:39Z | |
| dc.date.issued | 2009 | |
| dc.department | Niğde ÖHÜ | |
| dc.description.abstract | An airport is like a complicated factory. Any problem that may happen in any situation can directly be a restrictive factor for the airport capacity. It is necessary to develop a reasonable model in which the time is considered between the plane lands and passengers get out of the airport. One of the most important issues in the capacity analysis of airports is check-in unit capacity analysis. Any airport must have enough number of check-in counters providing necessary and facilitated transportation that takes passengers and their luggage into account. In the literature there is limited work available including the capacity analysis of check-in units in airports to obtain a relation applicable to actual problem. In this work, two different approaches will be presented for the capacity analysis of check-in units of airports which includes many passengers intensively. One is artificial neural network (ANN) method and the other is fuzzy logic approach. ANN is an efficient method for the analysis of a broad range of engineering problems. In the current problem, an ANN structure predicts the functional time depending on the number of passengers and luggage affecting the capacity. Proposed ANN model is a dynamic model and is a new approach in capacity analysis of airports. A method of relationship is improved to be used in the check-in department with neural network education. Different ANN models have been used and a number of results have been obtained. Fuzzy logic approach is also extensively used in the analysis of many engineering problems in different disciplines. In the control mechanisms of events linguistic uncertainties may play a significant role. Fuzzy approach considers this role as in the key elements in human thinking. Besides ANN approach, this study also considers the capacity analysis of a check-in department in an airport with the view of those linguistic variables of number of passengers and their luggage adopted. Both ANN and Fuzzy Logic methods for the capacity analysis of check-in units in airports are used for the check-in unit analysis of a national airport (Antalya Airport). The results have shown both methods work well and as a result, required number of counters in the airport can be determined to provide passengers suitable and facilitated transportation. | |
| dc.identifier.endpage | 145 | |
| dc.identifier.isbn | 978-1-60692-393-1 | |
| dc.identifier.startpage | 123 | |
| dc.identifier.uri | https://hdl.handle.net/11480/5116 | |
| dc.identifier.wos | WOS:000269534700006 | |
| dc.identifier.wosquality | N/A | |
| dc.indekslendigikaynak | Web of Science | |
| dc.institutionauthor | Kiyildi, Recep Koray | |
| dc.language.iso | en | |
| dc.publisher | NOVA SCIENCE PUBLISHERS, INC | |
| dc.relation.ispartof | AIRPORTS: PERFORMANCE, RISKS, AND PROBLEMS | |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.title | CAPACITY ANALYSIS OF CHECK-IN UNITS IN AIRPORTS USING FUZZY LOGIC AND ARTIFICIAL NEURAL NETWORK APPROACHES | |
| dc.type | Article |
