Why in news?
The Indian Institute of Geomagnetism researchers have developed a model that will predict electronic density of ionosphere which is important for Communication and Navigation needs.
Details about the new model
- The new Artificial Neural Networks based global Ionospheric Model has been developed using long-term ionospheric observations to predict the ionospheric electron density and the peak parameters.
- The ionospheric variability is greatly influenced by both solar originated processes and the neutral atmosphere origin, therefore, difficult to model.
- Scientists have tried to model the ionosphere using theoretical and empirical techniques; however, the accurate prediction of electron density is still a challenging task.
More with respect to ANN
Artificial Neural Networks replicate the processes in the human brain to solve problems such as pattern recognition, classification, clustering, generalization, linear and nonlinear data fitting and time series prediction.
In recent years, the Artificial Neural Networks (ANNs) are showing potential to handle more complex and non-linear problems.
What is Ionosphere?
- Ionosphere is the ionized part of Earth’s upper atmosphere, from about 60 km (37 mi) to 1,000 km (620 mi) altitude, a region that includes the thermosphere and parts of the mesosphere and exosphere.
- The ionosphere is ionized by solar radiation, hence it grows and shrinks depending on the energy it absorbs from the Sun.
- It plays an important role in atmospheric electricity and forms the inner edge of the magnetosphere.
- It has practical importance because, among other functions, it influences radio propagation to distant places on the Earth.
- Due to the ability of ionized atmospheric gases to refract high frequency (HF, or shortwave) radio waves, the ionosphere can reflect radio waves directed into the sky back toward the Earth.
- This communication method is variable and unreliable, with reception over a given path depending on time of day or night, the seasons, weather, and the 11-year sunspot cycle.
