关键词: 熔渣, 活度, 遗传算法, 神经网络

Abstract: A model based on GA-NN for predicting the activity of components in multiple slag system is developed. The artificial neural nets (NN) can implement any approximation of function with simple structure, while the genetic algorithm (GA) is a globally optimized search one based on genetics and natural selection theory, which is available to implement the iteration process through allying the genetic manipulation to the individuals in colonies for their restructuring and then evolve the increasingly improved approximate solutions generation by generation in accordance to the adaptability function for individuals. GA is always used to give the weights and thresholds of neural nets. Computing and simulating the CaO-SiO2, CaO-SiO2-Al2O3 and CaO-SiO2-Al2O3-MgO slag systems, it is found that GA-NN model has high nonlinear capability and the computation results fit well with that in relevant earlier works, thus enabling the accurate prediction of the activity of components in molten slag.