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