B. Surekha, scholar P. R. Vundavilli, M. B. Parappagoudar and A. Srinath Professor of Mechanical Engineering have authored a paper and was published in International Journal of Cast Metals Research
A genetic fuzzy system has been developed to solve the forward and reverse mapping problems of green sand mould systems. The performance of a fuzzy logic (FL) system depends on its knowledge base, which consists of a database and a rule base. A binary coded genetic algorithm (GA) has been used to optimise the knowledge base for the FL based approaches. Two approaches have been developed for each model (i.e. forward and reverse modelling). In the first approach, a manually compiled database and rule base of the FL system are optimised by GA, whereas in the second approach, the GA is used to evolve the optimal FL system automatically. The membership function distributions of the FL system are assumed to be asymmetric triangular. The first approach is found to perform better than the latter in terms of accuracy in prediction of the responses.
Keywords: Green sand mould, Forward and reverse modelling, Asymmetric membership functions, Fuzzy logic, Genetic algorithm