NEURAL NETWORK MODELING AND GENETIC ALGORITHM FOR OPTIMIZING FORMULATION OF CATALYSTS

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NEURAL NETWORK MODELING AND GENETIC ALGORITHM FOR OPTIMIZING FORMULATION OF CATALYSTS

更新时间：2025-12-16

- NEURAL NETWORK MODELING AND GENETIC ALGORITHM FOR OPTIMIZING FORMULATION OF CATALYSTS
- CIESC Journal Issue 4, (1999)
- 作者机构：
  
  北京轻工业大学自动化工程系,北京,100037
- 作者简介：
- 基金信息：
- DOI：
  CLC： Q426
- Online First：25 August 1999，
  
  Published：25 August 1999
- 稿件说明：
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韩力群. NEURAL NETWORK MODELING AND GENETIC ALGORITHM FOR OPTIMIZING FORMULATION OF CATALYSTS[J]. CIESC Journal, 1999, (4).
DOI：

韩力群. NEURAL NETWORK MODELING AND GENETIC ALGORITHM FOR OPTIMIZING FORMULATION OF CATALYSTS[J]. CIESC Journal, 1999, (4). DOI：

摘要

采用神经网络对催化剂配方实验数据建模

在网络模型仿真实验的基础上应用遗传算法对配方组成进行优化

得到的优化配方经实验验证

证实了该算法的实际应用意义.该算法对化工产品的配方及工艺优化也有实用意义.

Abstract

Neural network is used for the modeling of experiment data. Based on simulation data from the neural network

GA is applied to optimize the formulation of catalysts. The optimizing formulations are proved by experiments and it is identified that the algorithm is practicable . GA can also be used in optimizing formulations and optimizing chemical processes.

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