ENHANCED WEIGHT OPTIMIZED RECURRENT NEURAL NETWORKS BASED ON SINE COSINE ALGORITHM FOR WAVE HEIGHT PREDICTION
Constructing offshore and coastal structures with the highest level of stability and lowest cost, as well as the prevention of faulty risk, is the desired plan that stakeholders seek to obtain.
Saved in:
| Main Author: | ALQUSHAIBI, ALAWI ALI ALI MANEA |
|---|---|
| Format: | Thesis |
| Language: | English |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-utpedia.22719 / |
| Published: |
2021
|
| Subjects: | |
| Online Access: |
http://utpedia.utp.edu.my/22719/1/ALAWI%20ALI%20ALI%20MANEA%20ALQUSHAIBI_1800055.pdf http://utpedia.utp.edu.my/22719/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Enhanced weight-optimized recurrent neural networks based on sine cosine algorithm for wave height prediction
by: Alqushaibi, A., et al.
Published: (2021) -
Towards Enhancing the Performance of Grid-Tied VSWT via Adopting Sine Cosine Algorithm-Based Optimal Control Scheme
by: Shutari, H., et al.
Published: (2021) -
Wave Height and Peak Wave Period Prediction Using Recurrent Neural Networks
by: Osawa, K., et al.
Published: (2020) -
A Review of Weight Optimization Techniques in Recurrent Neural Networks
by: Alqushaibi, A., et al.
Published: (2020) -
NEURAL NETWORK BASED ON ADAPTIVE MULTILAYERED PARTICLE
SWARM OPTIMIZATION FOR PIPELINE CORROSION PREDICTION
by: LEE , KIEN EE
Published: (2018)