title: Adaptive Neuro-Fuzzy Determination of the Effect of Experimental Parameters on Vehicle Agent Speed Relative to Vehicle Intruder.
abstract: Intelligent Transportation Systems rely on understanding, predicting and affecting the interactions between vehicles. The goal of this paper is to choose a small subset from the larger set so that the resulting regression model is simple, yet have good predictive ability for Vehicle agent speed relative to Vehicle intruder. The method of ANFIS (adaptive neuro fuzzy inference system) was applied to the data resulting from these measurements. The ANFIS process for variable selection was implemented in order to detect the predominant variables affecting the prediction of agent speed relative to intruder. This process includes several ways to discover a subset of the total set of recorded parameters, showing good predictive capability. The ANFIS network was used to perform a variable search. Then, it was used to determine how 9 parameters (Intruder Front sensors active (boolean), Intruder Rear sensors active (boolean), Agent Front sensors active (boolean), Agent Rear sensors active (boolean), RSSI signal intensity/strength (integer), Elapsed time (in seconds), Distance between Agent and Intruder (m), Angle of Agent relative to Intruder (angle between vehicles °), Altitude difference between Agent and Intruder (m)) influence prediction of agent speed relative to intruder. The results indicated that distance between Vehicle agent and Vehicle intruder (m) and angle of Vehicle agent relative to Vehicle Intruder (angle between vehicles °) is the most influential parameters to Vehicle agent speed relative to Vehicle intruder.
authors.affiliation: Department of Computer System and Information Technology, Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia.
authors.forename: Shahaboddin
authors.initials: S
authors.lastname: Shamshirband
authors.affiliation: Department of Automation and Robotics, Faculty of Electrical Engineering, University of Tuzla, Tuzla, Bosnia and Herzegovina.
authors.forename: Lejla
authors.initials: L
authors.lastname: Banjanovic-Mehmedovic
authors.affiliation: Department of Automation and Robotics, Faculty of Electrical Engineering, University of Tuzla, Tuzla, Bosnia and Herzegovina.
authors.forename: Ivan
authors.initials: I
authors.lastname: Bosankic
authors.affiliation: Department of Telecommunication, Faculty of Electrical Engineering, University of Tuzla, Tuzla, Bosnia and Herzegovina.
authors.forename: Suad
authors.initials: S
authors.lastname: Kasapovic
authors.affiliation: Department of Computer System and Information Technology, Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia.
authors.forename: Ainuddin Wahid Bin
authors.initials: AW
authors.lastname: Abdul Wahab
mesh_terms: D000465:Algorithms; D017143:Fuzzy Logic; D008962:Models, Theoretical; D018986:Motor Vehicles; D016571:Neural Networks, Computer