A novel reinforcement learning based tuna swarm optimization algorithm for autonomous underwater vehicle path planning-Reference-Cited by-同舟云学术

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A novel reinforcement learning based tuna swarm optimization algorithm for autonomous underwater vehicle path planning

Published:2023-07 Issue: Volume:209 Page:55-86
ISSN:0378-4754
Container-title:Mathematics and Computers in Simulation
language:en
Short-container-title:Mathematics and Computers in Simulation

Author:

Yan Zheping,Yan Jinyu^ORCID,Wu Yifan,Cai Sijia,Wang Hongxing

Funder

National Natural Science Foundation of China

Harbin Engineering University

Science Fund for Distinguished Young Scholars of Hebei Province

Publisher

Elsevier BV

Subject

Applied Mathematics,Modeling and Simulation,Numerical Analysis,General Computer Science,Theoretical Computer Science

Reference51 articles.

1. INFO: An efficient optimization algorithm based on weighted mean of vectors;Ahmadianfar;Expert Syst. Appl.,2022

2. An improved ant colony optimization algorithm based on particle swarm optimization algorithm for path planning of autonomous underwater vehicle;Che;J. Ambient Intell. Humaniz. Comput.,2020

3. Path planning of AUV during diving process based on behavioral decision-making;Chen;Ocean Eng.,2021

4. Modified central force optimization (MCFO) algorithm for 3D UAV path planning;Chen;Neurocomputing,2016

5. Optimal time-consuming path planning for autonomous underwater vehicles based on a dynamic neural network model in ocean current environments;Chen;IEEE Trans. Veh. Technol.,2020

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