02037nab a22002897a 4500 OSt 20250506070019.0 250505t2021 |||||||| |||| 00| 0 eng d 2349-5162 JMCFI - Learning Resource Center Gorres-Abato, Teotima Evangelista 31554 A stochastic dynamical system model of an earthquake in Agusan del Sur Region : genetic programming based symbolic regression / Teotima Evangelista Gorres-Abato. s.l. : Elsevier., Inc. 2021. Abstract : 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. Earthquake symbolic regression Agusan del Sur. 31564 Earthquake genetic programming Agusan del Sur. 31565 Stochastic process. 31566 Stochastic process. 31566 Dynamical system. 31560 Evolutionary algorithm. 31567 Research. 146 Quantitative research. 1581 Journal articles (Open access). 11480 , volume 8, issue 6 (May 2021). Journal of Emerging Technologies and Innovate Research (JETIR) https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3869617 OAER 0 lcc 9900 9900 0 0 0 0 DL DL 2025-05-06 0 2025-05-06 https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3869617 2025-05-06 OAER