An ANFIS Based Vehicle Sales Forecasting Model Utilizing Feature Clustering and Genetic Algorithms
| dc.authorid | 110138 | en_US |
| dc.authorid | 21327 | en_US |
| dc.contributor.author | Yılmaz, Atınç | |
| dc.contributor.author | Kaya, Umut | |
| dc.contributor.author | Şaykol, Ediz | |
| dc.date.accessioned | 2021-01-21T12:41:58Z | |
| dc.date.available | 2021-01-21T12:41:58Z | |
| dc.date.issued | 2020 | |
| dc.department | İstanbul Beykent Üniversitesi | en_US |
| dc.description.abstract | The automotive sector is one of Turkey’s most important industries, and the developments in technology are affecting the automotive sector as well as the other sectors. The methods that have been used to date indicate that the use of AI should be increased when the demand forecasting applications take into account the developments in the industry. For this purpose, by using the data taken from the Automotive Distributors Association and Turkish Statistical Institute Internet pages, intuitive learning hybrid ANFIS method is used to forecast the sales in this study. A clustering scheme is first applied to group the features, and then the features are fed into genetic algorithms to improve the prediction model performance. The experiments show that the prediction performance of the proposed method is good when compared to existing related studies in the literature. | en_US |
| dc.identifier.citation | Journal Of Aeronautıcs And Space Technologıes, V13, S1, 2020 | en_US |
| dc.identifier.issn | 1304-0448 | |
| dc.language.iso | en | en_US |
| dc.publisher | Hezarfen Aeronautics and Space Technologies Institute | en_US |
| dc.relation.publicationcategory | Makale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| dc.subject | Adaptive Neuro Fuzzy Inference System (ANFIS) | en_US |
| dc.subject | Feature Clustering | en_US |
| dc.subject | Genetic Algorithms | en_US |
| dc.subject | Vehicle Sales Prediction | en_US |
| dc.title | An ANFIS Based Vehicle Sales Forecasting Model Utilizing Feature Clustering and Genetic Algorithms | en_US |
| dc.type | Article | en_US |
