Personal Information

  • Master Tutor
  • (Associate Professor)
  • Name (Pinyin):

    baiyan
  • School/Department:

    理学院
  • Education Level:

    PhD student
  • Gender:

    Female
  • Contact Information:

    yb_xauat@126.com
  • Degree:

    Doctoral degree
  • Professional Title:

    Associate Professor
  • Status:

    Employed
  • Academic Titles:

    大数据科学系主任,曾任大数据科学系党支部书记
  • Alma Mater:

    西安建筑科技大学
  • Discipline:

    Mathematics

Other Contact Information

  • Email:

The analysis of combined prediction model of building energy consumption with grey theory and RBF neural network

  • Release time:2024-08-09
  • Hits:
  • Affiliation of Author(s):

    理学院
  • Journal:

    Advanced Materials Research
  • Key Words:

    中文关键字:建筑能耗;GM(1,1)模型;径向基神经网络,英文关键字:Building Energy Consumption;GM(1,1) Model;Radial B
  • Abstract:

    A kind of new combined modeling method with GM(1,1) and RBNN (Radial Basis Neural Network) is brought forward, according to the idea that the method of neural network can bring grey prediction model a good modified effect. Based on the analysis of the energy consumption data of the existing and the annually-increased building area, the GM(1,1) model was then constructed. And the RBF neural network was used for the model residual error revising. The simulation and experiment results show that the novel model is more effective than the common grey model.
  • Note:

    白燕
  • Co-author:

    蒋红梅
  • First Author:

    任庆昌,baiyan
  • Indexed by:

    Journal paper
  • Volume:

    卷:374-377
  • Issue:

    期:
  • Page Number:

    页:90-93
  • Translation or Not:

    no
  • Date of Publication:

    2011-12-01
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