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This paper uses GMDH method to establish a prediction model to forecast the vehicles for business transport of Guangxi in China, since the original samples of the output value of transport & storage of Guangdong are less enough to be used with the traditional methods. Compared with traditional linear regression and artificial neural network, the predicted results show that GMDH method is an effective...
This paper uses GMDH method to establish a prediction model to forecast the output value of transport & storage of Guangdong in China, since the original samples of the output value of transport & storage are less enough to be used with the traditional methods. Compared with traditional linear regression and artificial neural network, the predicted results show that GMDH method is an effective...
Prediction models based on different concepts have been proposed in recent years. The accuracy rates resulting from linear models such as exponential smoothing, linear regression (LR) and autoregressive integrated moving average (ARIMA) are not high as they are poor in handling the nonlinear relationships among the data. Neural network models are considered to be better in handling such nonlinear...
The purpose of this study is to investigate the data fitting for broiler growth performance parameters. In this paper, the gradual advancing analysis methods, from correlation analysis, multiple linear regression, to neural network, are proposed. The mean technology roadmap is: firstly, correlation analysis is used to detect the degree of correlation between the broiler growth performance parameter...
Linear regression model is widely used in data stream prediction processing. In order to eliminate the prediction deviation caused by small data set, curve tendency correction technique is used to increase the prediction accuracy. Firstly the weighted moving method is used to modify the prediction function parameters. This algorithm improves the predicting accuracy, but causes low efficiency of time...
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