A hybrid reasoning system for supporting estuary modelling

In this paper the development of a Case-Based reasoning system for Estuarine Modelling (CBEM) is presented. The aim of the constructed CBEM system is to facilitate the utilisation of complex modelling software by users who lack detailed knowledge about modelling techniques and require training and assistance to implement sophisticated schemes effectively. The system is based on modern computing methods and is constructed as a hybrid of three modules which operate conjunctively to guide the user to obtain the best possible simulation for realistic problems. These modules are: a case-based reasoning scheme a genetic algorithm and a library of numerical estuarine models. Based on the features of a given estuary and the physical phenomenon to be modelled, an appropriate solution algorithm from the system’s library is retrieved by the case-based module after a specifically designed reasoning process. The selected model is then analysed and further treated by the genetic algorithm component to find optimum parameters which can appropriately model the conditions and characteristics of any given estuary. Finally, the user is provided with a procedure that gives the best solution for a problem using the available hydrographic data and under the specified conditions. As an illustrative example and to show the applicability of the present CBEM system under realistic conditions a case study based on the simulation of salinity distribution in the Tay estuary (Scotland, UK) is given in this paper.