A Fast Global Fuzzy Clustering Algorithm for the Chemical Gray Box Modeling

WANG Li; CHEN Shu-xin; JING Tao

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A Fast Global Fuzzy Clustering Algorithm for the Chemical Gray Box Modeling

更新时间：2026-07-10

- A Fast Global Fuzzy Clustering Algorithm for the Chemical Gray Box Modeling
- Vol. 15, Issue 3, Pages: 31-35(2010)
- 作者机构：
  
  1. 齐齐哈尔大学计算中心
  2. 齐齐哈尔大学化学与化学工程学院
- 作者简介：
- 基金信息：
- DOI：
  CLC： TQ015;TP391.9
- Published：2010
- 稿件说明：
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WANG Li, CHEN Shu-xin, JING Tao. A Fast Global Fuzzy Clustering Algorithm for the Chemical Gray Box Modeling[J]. 2010, 15(3): 31-35.
DOI：

WANG Li, CHEN Shu-xin, JING Tao. A Fast Global Fuzzy Clustering Algorithm for the Chemical Gray Box Modeling[J]. 2010, 15(3): 31-35. DOI：

摘要

针对化工过程灰箱建模存在的精确度差、速度慢、计算复杂度高等问题

对现行模糊C-均值聚类算法进行了改进

提出了一种快速全局优化的(用于建模的数据训练集)模糊聚类算法.该算法具有不依赖初始条件、收敛速度快等特点.实验结果表明

利用快速全局优化模糊聚类算法得到的数据

在灰色预测的时间和数据准确性方面都有了显著提高

计算机仿真实验表明了该算法的有效性.

Abstract

The modeling of chemical grey box has the problems of low accuracy

slow and high degree of computational complexity.The Fast Global Fuzzy C-Means Clustering algorithm(FGFC)

based on the Fuzzy C-means algorithm

is improved(It is used to get effective training data of modeling).The algorithm does not depend on initial conditions

convergence speed and so on.Experiments show that the FGFCM algorithm’s data has improved the performance of predicting time and data accuracy.This algorithm is proved to be efficient...

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