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Earth Planets Space, 64, 473483, 2012TEC prediction with neural network for equatorial latitude station in Thailand Kornyanat Watthanasangmechai1, Porch Supnithi1, Social Lerkvaranyu1, Tanya Tsugawa2, Custom
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How to fill out tec prediction with neural

01
Gather the dataset of TEC (Total Electron Content) measurements.
02
Preprocess the data by normalizing it and splitting it into training and testing sets.
03
Design a neural network architecture suitable for TEC prediction.
04
Train the neural network using the training dataset. Adjust the hyperparameters, such as learning rate, batch size, and number of epochs, to optimize the model's performance.
05
Evaluate the trained model using the testing dataset and calculate the prediction accuracy.
06
Fine-tune the model if necessary by tweaking the network architecture or providing more training data.
07
Once satisfied with the model's performance, use it to make predictions on new TEC data by feeding the data into the trained network.
08
Monitor and analyze the predictions to gain insights and improve future predictions.

Who needs tec prediction with neural?

01
Researchers and scientists studying the Earth's ionosphere and its effects on communication systems.
02
Weather forecasters and meteorologists who need accurate TEC predictions for space weather forecasting.
03
Satellite operators and space agencies who rely on TEC predictions for satellite navigation and communication systems.
04
Telecommunication companies involved in satellite communication and global positioning systems (GPS) that require precise TEC information for optimal performance.
05
Any individual or organization interested in understanding and predicting ionospheric conditions for various applications.
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