Authors :
Guruprasath.I; Vasanth.R; Vishnuvarthan.S; Jovin Deglus; Gopika. V; Kirubadevi. M
Volume/Issue :
Volume 7 - 2022, Issue 2 - February
Google Scholar :
http://bitly.ws/gu88
Scribd :
https://bit.ly/3vI1G7L
DOI :
https://doi.org/10.5281/zenodo.6331287
Abstract :
Air pollution is one of the foremost hazards of
environmental pollution. None of the living effects will
survive while not having similar air. still, as a result of
buses, agrarian conditioning, manufactories and diligence,
mining conditioning, burning of fossil energies our air is
carrying impure. This conditioning unfolds contaminant,
gas, monoxide, particulate adulterants in our air that are
dangerous for all living organisms. The air we tend to
breathe each moment causes numerous health problems.
thus, we want an honest system that predicts similar
profanations and is useful in an advanced atmosphere.
thus, then we tend to area unit prognosticating pollution
for our city exploitation data processing fashion. In our
model we tend to area unit exploitation data processing
J48 decision tree formula and K means algorithm. Our
system takes once and current information and applies
them to our model to prognosticate pollution. This model
reduces the complicatedness and improves the
effectiveness and utility and might give fresh dependable
and correct call for environmental city.
Keywords :
component; Air pollution prediction, Data mining, city, J48 decision tree, Complexity, Effectiveness, Practicable.
Air pollution is one of the foremost hazards of
environmental pollution. None of the living effects will
survive while not having similar air. still, as a result of
buses, agrarian conditioning, manufactories and diligence,
mining conditioning, burning of fossil energies our air is
carrying impure. This conditioning unfolds contaminant,
gas, monoxide, particulate adulterants in our air that are
dangerous for all living organisms. The air we tend to
breathe each moment causes numerous health problems.
thus, we want an honest system that predicts similar
profanations and is useful in an advanced atmosphere.
thus, then we tend to area unit prognosticating pollution
for our city exploitation data processing fashion. In our
model we tend to area unit exploitation data processing
J48 decision tree formula and K means algorithm. Our
system takes once and current information and applies
them to our model to prognosticate pollution. This model
reduces the complicatedness and improves the
effectiveness and utility and might give fresh dependable
and correct call for environmental city.
Keywords :
component; Air pollution prediction, Data mining, city, J48 decision tree, Complexity, Effectiveness, Practicable.
