Ionograms Scaling by Using the Convolutional Neural Network
| dc.contributor.author | Thananphat Thanakulketsarat | |
| dc.contributor.author | Thanomsak Sopon | |
| dc.contributor.author | Watid Phakphisut | |
| dc.contributor.author | Kornyanat Hozumi | |
| dc.contributor.author | Wannaree Wongtrairat | |
| dc.date.accessioned | 2026-05-08T19:20:03Z | |
| dc.date.issued | 2021-3-10 | |
| dc.description.abstract | Ionosphere in F layer has the most irregularity for phenomenon occurrence of amplitude scintillation which leads to the problem in the satellite signals. Ionosphere can be observed by Ionosonde to study F2 layer critical frequency (foF2) parameter and height of F layer (h'F) parameter from the ionogram. This paper presents the convolutional neural network (CNN) to determine foF2 and h'F parameters. The simulation start from passing the ionogram images to the proposed CNN model with 2,000 epoch training. The simulated accuracies of both foF2 and h'F parameters are equal to 92.8% and 98.4%, respectively. | |
| dc.identifier.doi | 10.1109/ieecon51072.2021.9440358 | |
| dc.identifier.uri | https://dspace.kmitl.ac.th/handle/123456789/17310 | |
| dc.subject | Neural Networks and Applications | |
| dc.subject | Sensor Technology and Measurement Systems | |
| dc.title | Ionograms Scaling by Using the Convolutional Neural Network | |
| dc.type | Article |