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In this we are going to do the Earthquake magnitude damage prediction using region and it has been carried out using the temporal sequence of historic seismic activities in combination with machine learning classifier. These parameters are based on geophysical fact distribution of characteristic earthquake magnitude and seismic quiescence.
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README.md

RICHTER-PREDICTION-PREDICTING-DAMAGE-CAUSED-BY-EARTHQUAKES

In this we are going to do the Earthquake magnitude damage prediction using region and it has been carried out using the temporal sequence of historic seismic activities in combination with machine learning classifiers. Prediction has been made based on mathematically calculated eight seismic indicators using the earthquake catalog of the area. These parameters are based on geophysical fact, distribution of characteristic earthquake magnitude and seismic quiescence. In this research the basic motto is “prediction of earthquake damage using machine learning” and the idea is to use existing data set of seismic activity for training and then to predict, when an earthquake will happen and how much damage will be use through it. In this study, we are using Random forest classifier for the implementation. In this we are going to do the Earthquake magnitude damage prediction using region and it has been carried out using the temporal sequence of historic seismic activities in combination with machine learning classifiers. Prediction has been made based on mathematically calculated eight seismic indicators using the earthquake catalog of the area. These parameters are based on geophysical fact, distribution of characteristic earthquake magnitude and seismic quiescence. In this research the basic motto is “prediction of earthquake damage using machine learning” and the idea is to use existing data set of seismic activity for training and then to predict, when an earthquake will happen and how much damage will be use through it. In this study, we are using Random forest classifier for the implementation.

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