Ship Attitude Prediction Model Based on Cross-Parallel Algorithm Optimized Neural Network-Reference-Cited by-同舟云学术

Ship Attitude Prediction Model Based on Cross-Parallel Algorithm Optimized Neural Network

Published:2022 Issue: Volume:10 Page:77857-77871
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Jiang Yanshu¹,Jia Mingqi¹^ORCID,Zhang Biao¹,Deng Liwei¹

Affiliation:

1. Heilongjiang Provincial Key Laboratory of Complex Intelligent System and Integration, School of Automation, Harbin University of Science and Technology, Harbin, China

Funder

Natural Science Foundation of Heilongjiang Province, China,

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09837905.pdf?arnumber=9837905

Reference35 articles.

1. Taylor–HHO algorithm: A hybrid optimization algorithm with deep long short‐term for malicious JavaScript detection

2. Using LSTM Neural Network Based on Improved PSO and Attention Mechanism for Predicting the Effluent COD in a Wastewater Treatment Plant

3. PSO–LSTM for short term forecast of heterogeneous time series electricity price signals

4. LSTM-Based Battery Remaining Useful Life Prediction With Multi-Channel Charging Profiles

5. An improved particle swarm optimization algorithm applied to long short-term memory neural network for ship motion attitude prediction

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