Abstract
As an approach to data mining, we focus on technologies for learning in neural net-works., In this paper, after explaining two discovery algorithms developed for modeling complex phenomena, we describe an approach to improving scientific models that are cast as sets of equations. As an application using these methods, we review one such model for aspects of the Earth ecosystem, then recount its application to revising parameter values, intrinsic properties, and functional forms, in each case achieving reduction in error on Earth science data while retaining the communicability of the original model.
