Application of Three Neural Network Models in the Prediction ofStratospheric Wind Field
Wind field forecast is of great significance for aerostat trajectory prediction. Traditional theoretical models can only predict wind speed in the next few hours, while BP neural network models can predict wind speeds in next few days. Therefore, in this paper, BP neural network, genetic algorithm-B...
Saved in:
| Main Authors: | YUAN Junjie, LUO Rubin, LIAO Jun, YANG Zechuan, WANG Ning, LI Jun |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Control and Information Technology
2019-01-01
|
| Series: | Kongzhi Yu Xinxi Jishu |
| Subjects: | |
| Online Access: | http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2019.05.003 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Short-term Wind Speed Prediction Based on Wavelet Packet Decomposition and BP Neural Network
by: WANG Ning, et al.
Published: (2019-01-01) -
Assessment of the Usefulness of Observation and Tracking Heads of the Long-Range for the Stratospheric Aerostat Recognition System
by: Paweł DOBRZYŃSKI, et al.
Published: (2018-12-01) -
Day–Night Energy-Constrained Path Planning for Stratospheric Airships: A Hybrid Level-Set Particle Swarm Optimization (LS-PSO) Framework in Dynamic Flows
by: Cheng Liu, et al.
Published: (2025-05-01) -
Long-term prediction of wind speed in La Serena City (Chile) using hybrid neural network-particle swarm algorithm
by: Juan A Lazzús, et al.
Published: (2017-01-01) -
Design of the Aerial Deceleration Phase of an Aerostat Considering the Deployment Scale
by: Jun Liao, et al.
Published: (2025-05-01)