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基于数据融合的铝电解电流效率因素最佳匹配
Alternative TitleBest Match of Influence Factors of Aluminum Electrolytic Current Eficiency Based on Data Fusion
孔磊; 王卓
Department信息服务与智能控制技术研究室
Source Publication计算机仿真
ISSN1006-9348
2015
Volume32Issue:5Pages:360-363, 415
Indexed ByCSCD
CSCD IDCSCD:5435098
Contribution Rank1
Funding Organization国家863项目(2013AA040705) ; 中国科学院重点部署项目(KGZD-EW-302)
Keyword电流效率 最佳匹配 数据融合 模糊聚类 支持度权重分配
Abstract铝电解过程电流效率的影响因素多且相互耦合,为提高电解槽性能,确保电流高效率运行,需确定各因素之间的最佳匹配。针对上述问题,提出一种基于支持度权重分配数据融合改进算法的方法。首先,利用减聚类改进的模糊C均值算法进行聚类;然后,结合聚类结果,针对传统支持度权重分配数据融合算法存在的问题进行改进,得到待融合的各聚类中心的权重,进而得到铝电解过程电流效率影响因素的最佳匹配。仿真结果表明,与传统的指标最优法和均值法比较,利用数据融合得到的电流效率因素最佳匹配更实用合理,且能有效地指导电解槽操作,以提高电流效率。
Other Abstractmany factors affect the current efficiency of Aluminum electrolysis process and ale mutually coupled, it needs to determine the best match between the factors to guide cell operation and ensure its high current efficiency.To solve the problem mentioned above, an improved support—degree based weight distribution data fusion method was proposed.First of all, the improved fuzzy C-means clustering algorithm with sub—clustering was used for clustering.Then, the weight of each factor of Clustering centers was determined according to the result of clustering, and the improved support-degree based weight distribution data fusion algorithm was applied to fuse the clustering centers, thereby the best match of influence factors was achieved.Finally, compared with traditional methods, this new method is more practical and reasonable, and Can guide more effectively the operation of the cell to improve the current efficiency.
Language中文
Citation statistics
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/16860
Collection信息服务与智能控制技术研究室
Affiliation1.中国科学院沈阳自动化研究所
2.中国科学院大学
3.中国科学院网络化控制系统重点实验室
Recommended Citation
GB/T 7714
孔磊,王卓. 基于数据融合的铝电解电流效率因素最佳匹配[J]. 计算机仿真,2015,32(5):360-363, 415.
APA 孔磊,&王卓.(2015).基于数据融合的铝电解电流效率因素最佳匹配.计算机仿真,32(5),360-363, 415.
MLA 孔磊,et al."基于数据融合的铝电解电流效率因素最佳匹配".计算机仿真 32.5(2015):360-363, 415.
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