A hybrid approach using decision tree and logistic regression for earthquake prediction

Tremor since the shaking of the external layer of the Earth coming about due to an unforeseen appearance of energy in the Earth’s lithosphere that causes seismic ripple effects. Quakes manifest themselves at the Earth’s surface by shaking and removing or upsetting the ground. So anticipating the variables of a seismic tremor is a difficult occupation as a quake doesn’t show explicit examples bringing about wrong forecasts. Methods dependent on AI are notable for their capacity to track down secret examples in information. The AI model is fabricated dependent on the past information connected with quakes where the model can gain the example from the information and takes thought of the elements. The elements which are thought-about the pre-handled information that is then subject to the elements are checked by the tremor. The correlation of AI calculations improves forecast and execution measurements are also determined and assessed.