Model of artificial neural network for complex data analysis in slag glass-ceramic
点击次数：发表时间：2025-05-23
- 所属单位：[1]Shenzhen Univ, Normal Coll, Dept Biol & Chem, Shenzhen 518060, Peoples R China;[2]Shenzhen Univ, Dept Sci & Technol, Shenzhen, Peoples R China;[3]Xian Univ Elect Sci & Technol, Coll Elect Engn, Xian, Peoples R China;[4]Univ Elect Sci & Technol, Coll Microelect & Solid Elect, Chengdu, Peoples R China
- 发表刊物：ZEITSCHRIFT FUR METALLKUNDE
- 关键字：Artificial Neural Network (ANN); complex data analysis; glass-ceramic
- 摘要：An artificial neural network was applied to slag glass-ceramic complex data analysis. A three-layer feedforward network was built with a new robust learning algorithm based on a concept of entire error modifying. These studies indicate that the network has an excellent learning ability when its topology is M - (2M + 1) - 1 and when an appropriate study error was chosen. Research shows that this slag glass-ceramic neural network is robust, accurate and stable in complex data analysis, and can disclose the relationship of elemental compositions, processing parameters and material properties of slag glass-ceramic effectively.
- 文献类型：Article
- 卷号：95
- 期号：2
- 页面范围：97-101
- ISSN号：0044-3093
- 是否译文：否
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- 性别：男
- 职称：教授
- 毕业院校：电子科技大学
- 学历：博士研究生毕业
- 学位：工学博士学位
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- 2012 当选： 新世纪优秀人才计划
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