Paper Title
Statistical Approach in Data Filtering for Prediction Vessel Movements Through Time and Estimation Route using Historical Ais Data

Abstract
The prediction of vessel maritime navigation has become an interesting topic in last years, especially in areas of economical commercial exchange and security. Also, vessels monitoring requires better systems and techniques that help enterprises and governments to protect they own interests. In specific, the prediction of vessels movements is important concerning safety and tracking. However, the applications of prediction techniques have a high cost of computational efficiency and low resource-saving. This article presents a method for select historical data on ship-specific routes to optimize the prediction of ship positions and its route estimation. These historical navigation data can help us to estimate a complete path and perform vessel positions predictions through time. Our results obtained are acceptable concerning route estimation with a precision of 74.98%, and with vessel positions predictions through time we got a 79% of accuracy. Keywords - Ships, Neural networks, e-navigation..