Comparative Performance Analysis of Particle Swarm Optimization and Artificial Bee Colony Algorithm for Optimization of Missile Gliding Trajectory-Reference-Cited by-同舟云学术

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Comparative Performance Analysis of Particle Swarm Optimization and Artificial Bee Colony Algorithm for Optimization of Missile Gliding Trajectory

Published:2022-12 Issue: Volume: Page:
ISSN:
Container-title:2022 OITS International Conference on Information Technology (OCIT)
language:
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Author:

Sahoo Shubhashree¹,Dalei Rabindra Kumar²,Rath Subhendu Kumar³,Sahu Uttam Kumar⁴

Affiliation:

1. Biju Patnaik University of Technology (BPUT),Department of Computer Science and Engineering,Rourkela,India

2. Silicon Institute of Technology (SIT),Department of Computer Science and Engineering,Bhubaneswar,India

3. Biju Patnaik University of Technology (BPUT),Rourkela,India

4. Defence Research Development Laboratory (DRDL), Defence Research Development Organization (DRDO),Hyderabad,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10053682/10053626/10053806.pdf?arnumber=10053806

Reference32 articles.

1. Ascent phase trajectory optimization for vehicle with multi-combined cycle engine based on improved particle swarm optimization;hongyu;Acta Astronaut,2017

2. Particle Swarm Optimization Applied to Ascent Phase Launch Vehicle Trajectory Optimization Problem

3. Hypersonic reentry trajectory planning by using hybrid fractional-order particle swarm optimization and gravitational search algorithm;khurram;Chin J Aeronaut,2021

4. A hybrid particle swarm optimization-gauss pseudo method for reentry trajectory optimization of hypersonic vehicle with navigation information model;yu;Aerosp Sci Technol,2021

5. Skip entry guidance using numerical predictor–corrector and patched corridor

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