Title :
An improved modeling of mode-choice behavior in urban area using adaptive neural fuzzy inference system
Author :
Goel, Shivani ; Sinha, Arun Kumar
Author_Institution :
Shobhit Univ., Meerut, India
Abstract :
This paper presents an improved model for mode-choice behavior analysis of work trips in urban area. It is observed that the mode-choice for work trips is largely influenced by the fleet size and the level-of-service. The proposed model is implemented using Adaptive Neural fuzzy Inference System for peak period of work trips in Delhi urban area. The machine learning result is found quite satisfactory with validation error being as low as 0.68%.
Keywords :
fuzzy reasoning; learning (artificial intelligence); neural nets; planning; traffic engineering computing; Delhi urban area; adaptive neural fuzzy inference system; fleet size; level-of-service; machine learning; mode-choice behavior analysis; transportation planning model; work trips peak period; Adaptation models; Computational modeling; Data models; Fuzzy logic; Mathematical model; Planning; Urban areas; Adaptive Neural Fuzzy Inference System (ANFIS).; Mode-choice;
Conference_Titel :
Computing for Sustainable Global Development (INDIACom), 2014 International Conference on
Conference_Location :
New Delhi
Print_ISBN :
978-93-80544-10-6
DOI :
10.1109/IndiaCom.2014.6828145
