A rough set data prediction method based on neural network evaluation and least squares fusion

被引：4
|
作者：
Xi Fei [1 ]
Sun Youfu [1 ]
Ruan Xuejun [2 ]
机构：
[1] Nanjing Forestry Univ, Coll Mat Sci & Engn, Nanjing 210000, Jiangsu, Peoples R China
[2] Nanjing Forestry Univ, Coll Art & Design, Nanjing 210000, Jiangsu, Peoples R China
来源：
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS | 2019年 / 22卷 / Suppl 5期
关键词：
Composite wall; Heat insulation; Rough set; Predictive analysis; HOT SUMMER; WALL;
D O I：
10.1007/s10586-018-2641-x
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
To improve precision of heat insulation performance analysis algorithm of composite wall in hot summer and cold winter zone, a kind of rough-set predicative analysis method for heat insulation performance of composite wall in hot summer and cold winter zone is put forward. Firstly, structure and parameter for three kinds of walls adopted in research of this Paper are provided and corresponding heat-insulation physical model and problems are described; secondly, introducing rough set, combining with its advantages in disposing uncertain and inaccurate and incomplete data, evaluation analysis for insulation performance of composite wall has been realized; finally, the validity of proposed method is verified by simulation experiment.
引用
收藏
页码：11641 / 11646
页数：6
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