Genetic Algorithm Based Forecasting Model for the Employment Demand of Major in English

Recently, the employment demand has been paid a lot of attention to so that the research with respect to the forecasting methods such as linear regression, artificial intelligence and the grey prediction method have been comprehensively investigated. Since the predictive focus and the characteristics of the methods are different, the outcomes of predictions cannot achieve the accuracy by simply hybridizing several methods or ignore the big prediction errors. In this paper, we propose a combined forecasting model of employment demand of student in the English major based on genetic algorithm. The combined forecasting model and the global searching ability of genetic algorithm can confirm the portfolio weights. The results show that it is feasible and effective to composite prediction model to forecast employment demand.