Reliable methods to predict membrane scaling and fouling are important tools in the control of these phenomena. This dissertation focuses on the development and application of methods to predict and prevent barium sulphate scaling and particulate ...

There has been an explosive growth of methods in recent years for learning (or estimating dependency) from data, where data refers to known samples that are combinations of inputs and corresponding outputs of a given physical system. The main subject addressed in this thesis is model induction from data for the simulation of hydrodynamic processes in the aquatic environment. Firstly, some currently popular artificial neural network architectures are introduced, and it is then argued that these devices can be regarded as domain knowledge incapsulators by applying the method to the generation...