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Erschienen in:
2014 | OriginalPaper | Buchkapitel
Gold Price Forecasting Based on RBF Neural Network and Hybrid Fuzzy Clustering Algorithm
verfasst von : Fengyi Zhang, Zhigao Liao
Erschienen in: Proceedings of the Seventh International Conference on Management Science and Engineering Management
Verlag: Springer Berlin Heidelberg
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This paper predicts good price based on RBF neural network employing hybrid fuzzy clustering algorithm. PCA technique has been used to integrate the 6 parameter dependent sub-variables of each TI (Technical Indicators, include MA, ROC, BIAS, D, K), which has been originated from the gold price before, and the results act as input. By employing a new hybrid fuzzy clustering algorithm, which is proposed by Antonios and George [10], K-Mean clustering algorithm and RBE algorithm, the predictions of price are yielded for each interval-n model. n refers to the number of predictions achieved by 1 operation. The most important conclusion indicates that the hybrid fuzzy clustering algorithm is superior to the general RBF central vector selecting algorithm mentioned above, in the aspects of MSE, P-Accuracy Rate and ROC.