An Efficient ELM Algorithm for GSM Vehicle Tracking
Intelligent Transportation System (ITS) provides service for the different transportation modes which favor information to the user. The road transportation applies the technology of information as well as communication. The cellular network provides the signal to track the location which is called as Global System for Mobile communication (GSM). For procuring location, Received Signal Strength (RSS) is received from GSM. To achieve the better performance, here I proposed the advanced technology of Artificial Neural Networks (ANNs) that is Extreme Learning Machine (ELM). The ELM provides a Single Hidden Layer Feed forward Neural networks (SLFNs) and it chooses the hidden nodes randomly for determining the weight for the output. Learning is an important factor for designing a computational and intelligent process while classifying, clustering and controlling the data for training. ELM provides the extreme speed of learning. The received signal is de-noised with Gabor filter and matched with map for obtaining the current position of the vehicle.
Anitha Rajalakshmi.R , Rajarajan.A , Praveena.A