FEM post-doctoral researcher Annukka Lehikoinen recently published a paper in Ecological Indicators in collaboration with reserchers from the Swedish University of Agricultural Sciences,
Using a machine learning approach, Lehikoinen and others evaluate the complex relationships between coastal fish and environmental conditions. The paper demonstrates the use of Bayesian network classifiers with structural learning from data to analyze probabilistic dependencies in large datasets.
The presented approach can provide useful insights to evaluating uncertainties in environmental datasets, which are crucial for implementing meaningful and cost-efficient management actions.
Read the full open access paper here.
Lehikoinen, A., Olsson, J., Bergström, L., Bergström, U., Bryhn, A., Fredriksson, R., & Uusitalo, L. (2019). Evaluating complex relationships between ecological indicators and environmental factors in the Baltic Sea: A machine learning approach. Ecological Indicators, 101, 117-125.