Natural calamities like earthquakes can cause massive destruction, which can

lead to losses of man and resources. This can make a country go back on years of

development. Now, as science and technology are evolving rapidly in every

sphere, disaster management is no different. Today, with the help of science and

technology, disasters can be gauged beforehand. This will help in warning the

governments, which in turn can save millions of lives and resources. Not only

this, but science can also help understand the level of damage caused and how to

reach the affected people. Learn more about Data Science Training in Pune

Machine learning

Knowing when an earthquake can hit, where to hit, and how much damage it can

cause, predictive analytics can come real handy. Now, this is becoming a

possibility because of machine learning techniques. Today, using machine

learning, scientists can make the algorithms to predict earthquakes by sifting

large data sets. Earthquakes are caused by shifts in tectonic plates, which release

energy that moves and quakes the ground. These days past seismic data is used to

predict the energy releases that may cause earthquakes.

Earth and ML research

Some of the recent research and solutions for predicting earthquakes and their

after-effects are:

 Appsilon data science: they have used a machine learning program

called PyTorch to devise an algorithm that will help assess and predict

structural damage after earthquakes.

 Boston University, University of Cambridge, and Los Alamos

national laboratory: they have found a signal that emanates during

earthworks. This is then used to train the ML algorithms to predict

earthquakes.

 Columbia University: they are using machine learning by training

algorithms using geothermal earthquake data from the geysers to

categorize earthquakes.

 Google and Harvard: have created a neural network that is capable of

estimating the aftershock locations precisely.

P and S waves

P waves are primary waves that are the fort wave that is recorded by

seismometers. These waves are less destructive, as they apply force in the

direction of their movement. S waves, on the other hand, are more destructive

and are called shear waves. It applies force in 90 degrees to its direction of

movement and is quite difficult to register. Stanford researchers have created

earthquake transformers using machine learning to detect the S waves. This

transformer has worked in Japanese Tottori’s earthquake.

Low-frequency waves

Other than P and S waves, there are also low-frequency waves that are produced

in an earthquake. These low-frequency waves do not cause much damage, but

they can still travel to farther locations. MIT researchers have come up with a

neural network that is trained using various seismic data. A neural network is

capable of studying earthquakes P and S waves to predict the low-frequency

waves.

Machine learning and data science of late has shown huge growth in various

industries. It has helped find data patterns and also helps predict various

circumstances. Earthquake prediction helps save millions of lives and helps

create a better strategy for creating seismic safe infrastructure. Click here for more details Data Science Training in Chennai