• Teotima Evangelista Gorres

The study proposes a new approach to genetic programming (GP) based on symbolic regression (SR) on a statistical search which is a topological dynamical system identification technique that uses a stochastic process for finding the earthquake models from the space (phase or state space) and the law of evolution of such functions or models in a dynamical system. It is an evolutionary algorithm aimed to recapitulate a set of measures in an n- dimensional space, used to determine the relationship of measurable functions or model (sets of functions or distributions) and parameters simultaneously unlike in traditional regression analysis only the parameters are determined while the model is defined in advanced. Since the occurrence of an earthquake cannot be predict, this study introduce an earthquake model of Agusan Del Sur.

Symbolic regression, stochastic process, earthquake, topological dynamical system, dynamical system, evolutionary algorithm, and genetic programming

"A STOCHASTIC DYNAMICAL SYSTEM MODEL OF AN EARTHQUAKE IN AGUSAN DEL SUR REGION: GENETIC PROGRAMMING BASED SYMBOLIC REGRESSION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 6, page no.b477-b479, June-2021, Available :http://www.jetir.org/papers/JETIR2106205.pdf

"A STOCHASTIC DYNAMICAL SYSTEM MODEL OF AN EARTHQUAKE IN AGUSAN DEL SUR REGION: GENETIC PROGRAMMING BASED SYMBOLIC REGRESSION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 6, page no. ppb477-b479, June-2021, Available at : http://www.jetir.org/papers/JETIR2106205.pdf