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

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 par...

Full description

Saved in:
Bibliographic Details
Published in:Cluster computing 2019-09, Vol.22 (Suppl 5), p.11641-11646
Main Authors: Fei, Xi, Youfu, Sun, Xuejun, Ruan
Format: Article
Language:English
Subjects:
Algorithms
Approximation
Computer Communication Networks
Computer Science
Construction
Energy conservation
Energy consumption
Fuzzy sets
Heat transfer
Industrialized nations
Insulation
Knowledge representation
Neural networks
Operating Systems
Processor Architectures
Random variables
Summer
Temperature
Winter
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:1386-7857
1573-7543
DOI:10.1007/s10586-018-2641-x