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Volume 38 Issue 3
Jun.  2020
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Article Navigation >  ENVIRONMENTAL ENGINEERING  > 2020  >  38(3): 9-14,38
XUE Tong-lai, ZHAO Dong-hui, HAN Fei. SVR WATER QUALITY PREDICTION MODEL BASED ON GA OPTIMIZATION[J]. ENVIRONMENTAL ENGINEERING , 2020, 38(3): 123-127. doi: 10.13205/j.hjgc.202003021
Citation: LOU Dai, ZHANG Guang-zhi, REN Fu-min, XI Cheng-gang. ESTABLISHMENT OF QUANTITATIVE PREDICTION MODEL BASED ON CHARACTERISTICS OF WASTE GENERATED IN UNDERGROUND PIPELINE GALLERY CONSTRUCTION[J]. ENVIRONMENTAL ENGINEERING , 2020, 38(3): 9-14,38. doi: 10.13205/j.hjgc.202003002
shu

ESTABLISHMENT OF QUANTITATIVE PREDICTION MODEL BASED ON CHARACTERISTICS OF WASTE GENERATED IN UNDERGROUND PIPELINE GALLERY CONSTRUCTION

doi: 10.13205/j.hjgc.202003002

  • 1. Hongrun Construction Group Co., Ltd, Ningbo 315000, China;

  • 2. Beijing Jiaotong University, Beijing 100044, China;

  • 3. Zhonglu Gaoke Traffic Science and Technology Group Co., Ltd, Beijing 100088, China

  • Received Date: 2019-11-27
    Abstract
  • In this paper, the construction of the underground pipe gallery in Ningbo, Zhejiang province was taken as the research object. Based on the field investigation and the tracking of the construction progress, the quantitative prediction models of three kinds of construction wastes, including engineering slag, waste concrete and engineering slurry, were established. The predicted results showed that 83891.21 m3 of waste soil, 4837.34 m3 of waste concrete and 11435.27 m3 of engineering mud were expected to be produced. Compared with the real value, the relative errors of the model were 8.6%, 4.9%, 3.5% respectively, which were all lower than 20%. Thus, three kinds of construction waste prediction models were proved to be effective.
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