Abstract
Neural network is an intelligent method in conditon trend prediction, while the condition trend prediction is important to guarantee the safe operation of large equipments. In order to overcome the deficiency of basically the same probability contribution of neural network input to output predicted, this paper proposes an intelligent prediction method based on information entropy weighted neural network, taking Elman neural network as the basis, combining with information entropy theory to construct the prediction model based on information entropy weighted Elman neural network. Condition trend prediction results of the flue gas turbine showed that the proposed new method has better prediction precision and real time performance.
National Natural Science Foundation of China (50975020) and Funding Project (PHR20090518) for Academic Human Resources Development in Institutions of Higher Learning under the Jurisdiction of Beijing Municipality.
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Chen, T., Xu, Xl., Wang, Sh. (2011). An Intelligent Prediction Method Based on Information Entropy Weighted Elman Neural Network. In: Chen, R. (eds) Intelligent Computing and Information Science. ICICIS 2011. Communications in Computer and Information Science, vol 135. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18134-4_23
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DOI: https://doi.org/10.1007/978-3-642-18134-4_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-18133-7
Online ISBN: 978-3-642-18134-4
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