DYNAMICALLY MODELLING FOR MEDIUM SPEED COAL PULVERIZER BASED ON NEW TYPE RBF NEURAL NETWORK

HAO Yong-sheng1; ZHANG Ke2; LI Jun31.South-East China University

doi:10.19666/j.rlfd.2007.12.005

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DYNAMICALLY MODELLING FOR MEDIUM SPEED COAL PULVERIZER BASED ON NEW TYPE RBF NEURAL NETWORK

Thermal Power Generation Issue 12, Pages: 14-18(2007)

更新时间：2025-09-28

- DYNAMICALLY MODELLING FOR MEDIUM SPEED COAL PULVERIZER BASED ON NEW TYPE RBF NEURAL NETWORK
- 作者机构：
  
  1. 东南大学
  2. 烟台龙源电力技术有限公司
  3. 西安热工研究院有限公司
- 作者简介：
- 基金信息：
- DOI：10.19666/j.rlfd.2007.12.005
  CLC： TD453;TP183
- Published：2007
- 稿件说明：
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HAO Yong-sheng1, ZHANG Ke2, LI Jun31.South-East China University. DYNAMICALLY MODELLING FOR MEDIUM SPEED COAL PULVERIZER BASED ON NEW TYPE RBF NEURAL NETWORK[J]. Thermal Power Generation, 2007, (12): 14-18.
DOI：

HAO Yong-sheng1, ZHANG Ke2, LI Jun31.South-East China University. DYNAMICALLY MODELLING FOR MEDIUM SPEED COAL PULVERIZER BASED ON NEW TYPE RBF NEURAL NETWORK[J]. Thermal Power Generation, 2007, (12): 14-18. DOI： 10.19666/j.rlfd.2007.12.005.

摘要

提出了一种结合免疫聚类和免疫进化规划的径向基函数(RBF)神经网络设计方法

该方法采用人工免疫聚类机制根据输入数据集合自适应确定RBF神经网络隐节点的数量和数据中心位置

并通过提取核函数宽度作为疫苗和免疫选择操作确定网络输出层的权值。利用RBF神经网络设计方法建立了中速磨煤机出口温度和入口空气流量的RBF神经网络模型

仿真结果表明该模型具有较高的精度。

Abstract

A design method based on radial basic function(RBF) neural network combining immune flocking with immune evolution planning has been put forward. In this method

the number of indistinct nodal points and the centre position of data for RBF can be adaptively determined according to input data collection by adopting artificial immune flocking mechanism and the weight value from output layer of the network determined by taking the width of nuclear function as vaccine and selected operation for immune. Adopting the design method based on RBF neural netowork

a RBF network model for the outlet temperature and the outlet flow rate of a medium speed coal pulverizer has been established. Results of simulation show that the established model boasts higher accuracy.

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