Research on the Fuzzy Petri Net Optimization Modeling of Water Bloom Formation Process

WANG Xiao-yi; TANG Li-na; LIU Zai-wen; XU Ji-ping

doi:10.3969/j.issn.0372-2112.2013.01.013

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Research on the Fuzzy Petri Net Optimization Modeling of Water Bloom Formation Process

更新时间：2025-07-16

- Research on the Fuzzy Petri Net Optimization Modeling of Water Bloom Formation Process
- Acta Electronica Sinica Vol. 41, Issue 1, Pages: 68-71(2013)
- 作者机构：
  
  北京工商大学计算机与信息工程学院,北京,100048
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2013.01.013
  CLC： TH873.7
- Published：2013
- 稿件说明：
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WANG Xiao-yi, TANG Li-na, LIU Zai-wen, et al. Research on the Fuzzy Petri Net Optimization Modeling of Water Bloom Formation Process[J]. Acta Electronica Sinica, 2013, 41(1): 68-71.
DOI：

WANG Xiao-yi, TANG Li-na, LIU Zai-wen, et al. Research on the Fuzzy Petri Net Optimization Modeling of Water Bloom Formation Process[J]. Acta Electronica Sinica, 2013, 41(1): 68-71. DOI： 10.3969/j.issn.0372-2112.2013.01.013.

摘要

在对湖库藻类水华形成机理深入研究的基础上

构建了描述藻类水华形成过程的Petri网机理模型

考虑影响藻类水华形成关键因子的综合作用机理

根据实验分析结论

通过构建模糊隶属度函数对Petri网机理模型中的库所信度进行模糊化处理

并采用粒子群算法对机理模型中涉及的权重进行优化率定

同时通过神经网络对机理模型库所信度进行自适应学习

实现了对藻类水华形成过程的机理建模和对藻类水华暴发的预测.

Abstract

The Petri-net is utilized to preliminarily construct the mechanism model for evolutionary process of water bloom on the bases of deep research of the mechanism of evolution of lake water bloom.Considering the integrated mechanism of water bloom that affects key factors for the formation of algal water bloom and the results of the experimental analysis

membership function is constructed to fuzzy the library reliability of the Petri-net mechanism model and particle swarm optimization is used to optimize the weight involving the mechanism model.Meanwhile

with the neural network adaptively learning the mechanism model reliability

mechanism modeling and prediction are realized for algae water bloom outbreak.

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