Skillful prediction of Indian Ocean Dipole index using machine learning models
In this study, we evaluated six machine learning models for their skill in predicting the Indian Ocean Dipole (IOD). The results based on the IOD index predictions at 1–8 month lead time indicate that the AdaBoost model with Multi-Layer Perceptron as the base estimator, AdaBoost(MLP), to perform bet...
Saved in:
Main Authors: | J.V. Ratnam, Swadhin K. Behera, Masami Nonaka, Kalpesh R. Patil |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2025-02-01
|
Series: | Applied Computing and Geosciences |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2590197425000102 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Improved bootstrap X¯ control chart for non-normally distributed data
by: Sukma Adi Perdana, et al.
Published: (2025-06-01) -
Novel models based on machine learning to predict the prognosis of metaplastic breast cancer
by: Yinghui Zhang, et al.
Published: (2025-02-01) -
Machine learning for predicting severe dengue in Puerto Rico
by: Zachary J. Madewell, et al.
Published: (2025-02-01) -
Machine learning-driven optimization for predicting compressive strength in fly ash geopolymer concrete
by: Maryam Bypour, et al.
Published: (2025-03-01) -
Leveraging machine learning to predict residential location choice: A comparative analysis
by: Vahid Noferesti, et al.
Published: (2025-03-01)