IJRDO - Journal of Computer Science Engineering (ISSN: 2456-1843) https://ijrdo.org/index.php/cse <p>Subjects covered in Computer Science and Engineering include: Computer Science; Scientific Computing; Wireless Networking; Network Modelling; Computational Science &amp; Engineering; Theoretical Computer Science; Biosystems Engineering; Machine Learning; Systems Biology &amp; Bioinformatics; Biostatistics; Data Mining; Data Analysis; Internet Computing &amp; Web Services; Information System Engineering; Quantum Computing; Nano Computing; Soft Computing; Artificial Intelligence; Digital Signal Processing, Cloud Computing; Robotics; Computer Graphics; Information Science; Medical Image Computing; Natural language Processing; Evolutionary Computation.<br><span style="font-size: 1.5em;"><strong> <span style="color: #fcbd0f; text-shadow: #666666 0px 0px 3px;">Current Impact Factor: 2.562</span></strong></span></p> en-US <p>Author(s) and co-author(s)&nbsp;jointly&nbsp;and severally represent and warrant that the Article is original with the author(s) and does not infringe any&nbsp;copyright or violate any other right of any third parties, and that the Article has not been published&nbsp;elsewhere.&nbsp;Author(s) agree to the terms that the <strong>IJRDO Journal</strong> will have the full right to remove the published article on any misconduct found in the published article.</p> editor@ijrdo.org (Naeem Akhtar) info@ijrdo.org (Naveen Malik) Sat, 27 Apr 2019 05:01:41 +0000 OJS http://blogs.law.harvard.edu/tech/rss 60 Trajectory Simplification Algorithm based on Structure Features https://ijrdo.org/index.php/cse/article/view/2812 <p>With the extensive use of location based devices, trajectories of various kind of moving objects can be collected. As time going on, the amount of trajectory data increases exponentially, which brings a series of problems in storage, transmission and analysis. Current trajectory compression algorithms mainly focus on position preserving, compress ratio and run efficiency, but neglect the movement features in trajectories. In this paper, we propose a novel three-stage trajectory compression algorithm based on moving direction of objects, internal fluctuation in trajectories and trajectory velocity, which takes full account of movement pattern and structure features in trajectories. Firstly, the raw trajectory is compressed based on moving direction and the velocity of the object. Then, the trajectory is further simplified according to internal fluctuation in raw trajectory. Comprehensive experiments on real dataset show that: not only the efficiency and effectiveness of the proposed work is better, but also the reservation of local movement features of moving objects and internal characteristic information in trajectories is more detailed.</p> Mingjun Zhu Copyright (c) 2019 IJRDO - Journal of Computer Science Engineering (ISSN: 2456-1843) http://creativecommons.org/licenses/by-nc-nd/4.0 https://ijrdo.org/index.php/cse/article/view/2812 Wed, 17 Apr 2019 08:33:44 +0000