A Novel Ensemble Earthquake Prediction Method (EEPM) by Combining Parameters and Precursors

A leading cause of death from natural disasters over the last 50years is witnessed by none other than earthquake occurrences which have a negative economic impact on world and claimed thousands lives years, causing devastation to properties. In this paper, novel Ensemble Earthquake Prediction Method (EEPM) proposed implemented produce strong learner (ensemble method) having better accuracy in prediction, less variance, errors. Data (parameters) continuous nature collected two countries, India Nepal, for five surveyor’s data (precursor) categorical three countries India, Kenya years specific earthquake-prone regions. The preprocessed generated combining parameters precursor data. EEPM focuses detecting accurate early signs an finding probability occurrence specified region, i.e., prediction robustness. results produced R 2 variance error comparison individual machine learning methods as well 87.8%, compared state-of-the-art ensemble methods. will alarm not only people society but also different organizations explain appropriate range magnitude dynamics earthquake.