Coal ash fusion temperature forecasting method based on construction-pruning mixed optimizing RBF (Radial Basis Function) network

Abstract

The invention discloses a coal ash fusion temperature forecasting method based on a construction-pruning mixed optimizing RBF (Radial Basis Function) network, which is characterized by comprising the following two stages of crude regulation and fine regulation: the crude regulation stage comprises the steps of dynamically increasing the number of hidden nodes according to a principle of enabling an energy function to be minimum, selecting corresponding sample input as a data center and stopping till the number of the hidden nodes meets a stopping criterion; the fine regulation stage comprisesthe steps of further regulating the structure and the parameters of the RBF network, which are obtained through the crude regulation by using a Gaussian regularization method, establishing the corresponding construction-pruning mixed optimizing RBF network on the basis of the chemical constituents of coal ash, and forecasting coal ash fusion temperature through the construction-pruning mixed optimizing RBF network. A construction-pruning mixed optimizing algorithm (CPHM) effectively integrates the advantages of a construction algorithm and a pruning algorithm, can not only dynamically regulate the number of the hidden nodes of the RBF network, but also enable the data center of the RBF network to change in a self-adaption way; and in addition, the invention has the advantages of smaller structure, better generalization capability and higher robustness.

Description

technical field [0001] The invention relates to a method for predicting the melting point of coal ash, in particular to a method for predicting the melting point of coal ash with a hybrid optimized RBF network which combines the advantages of a neural network construction algorithm and a pruning algorithm. Background technique [0002] The ash melting point has a great influence on the slagging characteristics and thermal efficiency of the boiler. Many countries have formulated indicators to judge the slagging characteristics of boilers based on the ash melting point. Some domestic power plants also use the ash melting point as an important indicator for measuring coal quality. For solid-state slagging boilers, it is usually necessary to burn coal with a higher ash melting point to prevent slagging in the furnace. When the coal ash deformation temperature is 50-100°C higher than the furnace outlet flue temperature, it will not cause slagging on the convective heating surface;...

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Problems solved by technology

[0006] Purpose of the invention: The purpose of the present invention is to provide a coal ash melting point prediction method based on the structure-pruning hybrid optimization RBF network for the problems of low accuracy of the existing ash melting point prediction method, unreasonable model structure, and weak generalization ability. , in order to achieve the purpose of high prediction accuracy, simplified network structure, good generalization ability and strong robustness

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