The Predicting Tree Growth App: an algorithmic approach to modelling individual tree growth

Abstract

PredictingTreeGrowth is free and open-source application software written in Python 3.7 that allows easy and fast development of predictive models using the Recurrent Neural Network (RNN)/Long Short-Term Memory (LSTM) framework. RNNs have an upgraded architecture able to capture tree growth mechanisms related to time ordering and size dependence. The motivation for this App is to demystify the use of Machine Learning algorithms and allow accessibility of Machine Learning algorithms by the scientific community. Its simple graphical user interface (GUI) provides straightforward tools for building predictive models with the RNN algorithm.Fil: Magalhaes, Juliana G. de S.. University of British Columbia; CanadáFil: Polinko, Adam P.. Mississippi State University.; Estados UnidosFil: Amoroso, Mariano Martin. Universidad Nacional de Río Negro. Sede Andina. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Kohli, Gursimran S.. University Fraser Simon; CanadáFil: Larson, Bruce C.. University of British Columbia; Canad