Abstract:
Traffic jam is a major problem in Dhaka City, so a traffic management support system, with less
cost, flexible, easily maintainable and secured is in demand. For monitoring road traffic
condition, Internet based real time bi-directional communication provides a lot of benefits. For
making traffic system more realistic and reliable, dynamic route computation is a vital
requirement. Therefore, for predicting road weights, an integrated approach with multiple data
feeds and back propagation neural network with Levenberg Marquardt optimization is applied.
The traffic system where NN based dynamic weights computation is used and much more
suitable to find the optimal routes. Inclusion of BPNN with LM achieved more than 90%
accuracy. NARX time delay neural network is used to predit differet feature’s eights ad
those are applied in this neural network to determine the road weights of different roads. NARX
neural network performs better than weighted mean moving average to predict different
feature’s eights.
Description:
This thesis submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering of East West University, Dhaka, Bangladesh.