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

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Abstract

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.

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Acknowledgement

National sci-tech support plan: Integration and demonstration of green improved technology of Traditional timber structure farm house, No. 2015BAL03B03.

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Authors and Affiliations

  1. College of Materials Science and Engineering, Nanjing Forestry University, Nanjing, 210000, Jiangsu, China

    Xi Fei & Sun Youfu

  2. College of Art & Design, Nanjing Forestry University, Nanjing, 210000, Jiangsu, China

    Ruan Xuejun

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  1. Xi Fei
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  2. Sun Youfu
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  3. Ruan Xuejun
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Correspondence to Xi Fei.

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Fei, X., Youfu, S. & Xuejun, R. A rough set data prediction method based on neural network evaluation and least squares fusion. Cluster Comput 22 (Suppl 5), 11641–11646 (2019). https://doi.org/10.1007/s10586-018-2641-x

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  • DOI: https://doi.org/10.1007/s10586-018-2641-x

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