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Now showing items 1-8 of 8

#### Neurocontrol of a multi-effect batch distillation pilot plant based on evolutionary reinforcement learning

(2010)

The time cost of first-principles dynamic modelling and the complexity of nonlinear control strategies may limit successful implementation of advanced process control. The maximum return on fixed capital within the processing ...

#### Identification of nonlinearities in dynamic process systems

(2004)

Process modelling is an essential element in the development of advanced (model-based) process control systems, accounting for up to 80% of the cost of development. Often, models based on historic process data are the only ...

#### The development of a standalone computer simulation tool for the optimization of gypsum recovery at Afmine

(2005)

This paper describes the development and use of a process simulator to optimize gypsum recovery at Afmine, a small plant near Yzerfontein on the South African West Coast The simulator consisted of models of the major plant ...

#### Classification of process dynamics with Monte Carlo singular spectrum analysis

(2003)

Identification of non-linear systems can be a daunting task and in the process industries the problem is complicated considerably by the presence of noise from various sources, non-stationarity of the data and intermittence, ...

#### Development of an empirical model of a nickeliferous chromite leaching system by means of genetic programming

(1998)

By making use of genetic programming, empirical models for metallurgical processes can be evolved that are more cost-effective than models determined by means of classical statistical techniques. These methods explore ...

#### Non-linear system identification of an autocatalytic reactor using least squares support vector machines

(2003)

The concepts behind support vector machines are very interesting both in theory and in practice, as they are based on a universal constructive learning procedure derived from the statistical learning theory developed by ...

#### Modelling of rare earth solvent extraction with artificial neural nets

(1996)

The design and operation of mass transfer units such as rare earth solvent extraction systems require accurate models of the mass transfer phenomena that occur in these systems. The modelling of rare earth solvent extraction ...