Estimation and Forecasting of Ionospheric Total Electron Content Based on Neural Network and Hybrid Seasonal Autoregressive Integrated Moving Average-Neural Network

Unpredictable variability to total electron content (TEC) in the equatorial region and gaps in the TEC database due to Earth infrastructure failures creates a need to develop a TEC estimation model. NN-based approaches are found promising in modelling the ionospheric parameters because they have fle...

Full description

Saved in:
Bibliographic Details
Main Author: Vikneswary Jayapal
Format: Thesis
Language:en_US
Subjects:
Online Access:https://oarep.usim.edu.my/bitstreams/9b89933e-8290-4e22-83f6-c971f4083488/download
https://oarep.usim.edu.my/bitstreams/30a129c8-44bb-4412-8887-769909abd9e4/download
https://oarep.usim.edu.my/bitstreams/d994310b-d96d-49da-9981-45a6473508b8/download
https://oarep.usim.edu.my/bitstreams/1f6fc33e-123c-4ae6-be25-a4155cca9f24/download
https://oarep.usim.edu.my/bitstreams/34aebbad-ab30-40e1-a06f-bc10806b5d1a/download
https://oarep.usim.edu.my/bitstreams/f15200be-bc80-4b6b-9f23-24362197b721/download
https://oarep.usim.edu.my/bitstreams/a933a2ad-540d-4387-8959-db7f39463110/download
https://oarep.usim.edu.my/bitstreams/c07fa133-2bf4-481f-b0a2-70c29ac78282/download
Tags: Add Tag
No Tags, Be the first to tag this record!