This work proposes a novel approach to Soft Sensor modelling,
where the Soft Sensor is built by a set of experts which are artificial
neural networks with randomly generated topology. For each of
the experts a meta neural network is trained, the gating Artificial Neural
Network. The role of the gating network is to learn the performance of the
experts in dependency on the input data samples. The final prediction
of the Soft Sensor is a weighted sum of the individual experts predictions.
The proposed meta-learning method is evaluated on two different
process industry data sets
