Efficient use f artificial neural networks for path finding using fuzzy logic based Ant-Colony System algorithm

Path finding in major cities based on specific (or particular) requirements is one of the significant problems that city travellers face as well as a challenging demand or need for the car based navigation systems. Therefore, in this paper, we introduced a multi-parameter (taking more than one parameter into consideration) based path finding modern system which utilizes fuzzy logic to an Ant Colony System in the detection of optimum multi-parameter routes in terms of cost, distance etc. We made use of traffic data which we acquired by a traffic control online datasets and additional traffic data in the form of minutes are predicted (or forecasted) by employing (or applying) artificial neural networks (ANNs) to that. This proposed system has been virtually tested (or simulated) by taking the location: Sydney, Australia into consideration and the respective results are being evaluated. Addition to this, we tried to show the comparison analysis between the Ant Colony System based path (route) finding and Fuzzy-Logic Based Ant-Colony System.