Abstract— Artificial neural networks have proved an attractive approach to non-linear regression problems arising in environmental modelling, such as statistical downscaling, sh...
Gavin C. Cawley, Malcolm R. Haylock, Stephen R. Do...
Communication across the science-policy interface is complicated by uncertainty and ignorance associated with predictions on which to base policies. The international symposium ...
Abstract. This paper describes the problem of modelling toxicity of environmental pollutants using molecular descriptors from a systems theoretical viewpoint. It is shown that curr...
This paper introduces a generic theoretical framework for predictive learning, and relates it to data-driven and learning applications in earth and environmental sciences. The iss...
Vladimir Cherkassky, Vladimir M. Krasnopolsky, Dim...
— In many applications of supervised learning, the conditional average of the target variables is not sufficient for prediction. The dependencies between the explanatory variabl...