Abstract
In this paper, we apply ANFIS to the modeling of a forecasting system for the demand of teacher human resources. Because of its inherent distributive architecture and the efficient learning algorithms for adapting parameters, ANFIS has been shown to be very useful in nonlinear system modeling and in time series applications. After bring tested on a set of practical data, it reveals that the learning speed of the ANFIS model is faster than that of the gray model. In addition, the average prediction error of the ANFIS model, when compared with the gray model, is greatly reduced.
| Keywords: | ANFIS; adaptive neuro-fuzzy inference systems; forecasting model |
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