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International Journal of Scientific Development and Research - IJSDR
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Authors Name: Shabana M A , Elizabeth Isaac
Unique Id: IJSDR1805104
Published In: Volume 3 Issue 5, May-2018
Abstract: Mining trajectory data has been attracting significant interest in the last years. By analyzing trajectory data, we are able to discover the movement behavior and location aware knowledge, and then develop many interesting applications such as movement behavior discovery, location prediction, traffic analysis, and so on. In the proposed system it provides a framework of ship route mining thereby discovering the shortest path between source and destinations also detect the ships moving in a different path which is not similar to the frequently taken path. The shortest path (SP) problem concerns with finding the shortest path from a specific origin to a specified destination in a given network while minimizing the total cost associated with the path. Particle swarm optimization is a population based stochastic optimization technique inspired by the social behavior of bird flock. The proposed system uses the PSO based search method to obtain a best route from source to destination. The PSO starts with a population of particles whose positions, that represent the potential solutions for the studied problem, and velocities are randomly initialized in the search space. The search for optimal position (solution) is performed by updating the particle velocities. The different path taken by the ships may be due some terrorist attack or due to weather conditions. The system is to generate the optimum ships routes and detect the ships showing different pattern in their route.
Keywords: PSO (Particle Swarm Optimization), SP (Shortest Path)
Cite Article: "SHIP ROUTE MINING AND PATH OPTIMIZATION IN HADOOP", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.3, Issue 5, page no.676 - 682, May-2018, Available :http://www.ijsdr.org/papers/IJSDR1805104.pdf
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Publication Details: Published Paper ID: IJSDR1805104
Registration ID:180340
Published In: Volume 3 Issue 5, May-2018
DOI (Digital Object Identifier):
Page No: 676 - 682
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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