| 降低烧结固体燃耗的人工智能优化分析 |
| |
| 引用本文： | 张军红,谢安国,沈峰满. 降低烧结固体燃耗的人工智能优化分析[J]. 冶金能源, 2003, 22(4): 16-18,35 |
| |
| 作者姓名： | 张军红 谢安国 沈峰满 |
| |
| 作者单位： | 1. 鞍山科技大学
2. 东北大学 |
| |
| 摘 要： | 提出主成分分析法和BP神经网络相结合的方法，挖掘生产数据中的潜在关系。分析结果表明：某烧结机在现行原料条件下，降低固体燃耗不能单纯地提高或降低某个参数，而应在各工艺参数中寻求最佳的搭配。
|
| 关 键 词： | 烧结 固体燃耗 人工智能 主成分分析法 BP神经网络 数据挖掘 |
OPTIMIZING ANALYSIS ON DECREASING THE SOLID FUEL CONSUMPTION IN THE SINTERING PROCESS BY THE ARTIFICIAL INTELLIGENCE METHODS |
| |
| Zhang Junhong Xie Anguo. OPTIMIZING ANALYSIS ON DECREASING THE SOLID FUEL CONSUMPTION IN THE SINTERING PROCESS BY THE ARTIFICIAL INTELLIGENCE METHODS[J]. Energy For Metallurgical Industry, 2003, 22(4): 16-18,35 |
| |
| Authors: | Zhang Junhong Xie Anguo |
| |
| Affiliation: | Zhang Junhong Xie Anguo(Anshan University of Science and Technology) Shen Fengman(Northeastern University) |
| |
| Abstract: | Based on the analysis of the principle component and BP neural network,the relations among the productive datum were studied.The analysis results showed that in order to decrease the solid fuel consumption in the sintering process,it is better to find the best-suited relation among all parameters than only to increase or decrease some parameters value. |
| |
| Keywords: | principle component analysis BP neural network sintering solid fuel consumption |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
