Prediction of investment supply scale for higher education of China based on Levengerg-Marquardt algorithm
Linna Wei · Journal of Guangxi University · 2009
It is necessary to predict the investment supply scale to formulate the development program and determine the scale for higher education of China.Higher education investment supply is a non-linear system,and a good result can be achieved with a neural network.In order to increase the prediction performance,the training algorithm of neural network was improved.The principle of the Levengerg-Marquardt(L-M)algorithm was studied and analyzed in this paper.The L-M algorithm was used to predict the investment supply scale of higher education,and the entire prediction process was optimized.Experimental results indicated that the L-M optimization algorithm based investment supply scale prediction model in higher education showed faster converging speed and higer generalization ability.