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School trip production modeling using an improved adaptive-network-based fuzzy inference system

Shafahi, Y ; Sharif University of Technology | 2006

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  1. Type of Document: Article
  2. DOI: 10.1109/itsc.2006.1707436
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2006
  4. Abstract:
  5. Trip production has long been considered as a major element in trip demand estimation. Many models have been presented for this purpose. Models use socio-economic variables in order to predict trip production. This paper develops an Adaptive-Network-based Fuzzy Inference System (ANFIS) models to predict school trip production. ANFIS can construct an input-output mapping based on both human knowledge and stipulated input-output data pairs. In order to improve models' generalization capability, a heuristic algorithm is used to generate reasonable initial values for data loss in training data set. Models with different Membership Functions (MFs) were trained, validated and tested with real data obtained from Shiraz, a large city in Iran, and then compared with regression model made for school trip production. The results indicate that the Improved ANFIS (IANFIS) with Gaussian MF performed more accurate than the conventional regression model. © 2006 IEEE
  6. Keywords:
  7. Adaptive systems ; Computer simulation ; Heuristic algorithms ; Mathematical models ; Membership functions ; Regression analysis ; Adaptive-Network-based Fuzzy Inference System (ANFIS) ; Socio-economic variables ; Trip production ; Fuzzy inference
  8. Source: ITSC 2006: 2006 IEEE Intelligent Transportation Systems Conference, Toronto, ON, 17 September 2006 through 20 September 2006 ; 2006 , Pages 1501-1506 ; 1424400945 (ISBN); 9781424400942 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/1707436