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Forecasting urban construction waste generation utilizing the TI-TSTLNGM(1,1) Model based on the COOT Algorithm.

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  • 1College of Civil Engineering, Jiangxi Science and Technology Normal University, Nanchang, People's Republic of China.

Environmental Technology
|June 3, 2025
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Summary

This study introduces an enhanced grey model to accurately forecast construction waste (C&W) generation. The novel method improves prediction accuracy for better waste management planning.

Keywords:
COOT optimization algorithmConstruction waste generationdata volatilitygrey prediction modelresource management

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Area of Science:

  • Environmental Science
  • Civil Engineering
  • Data Science

Background:

  • Accurate estimation of construction waste (C&W) generation trends is challenging due to data volatility and incompleteness.
  • Existing forecasting methods often lack the precision needed for effective waste management planning.

Purpose of the Study:

  • To develop a novel forecasting method and an enhanced grey model for scientifically estimating and predicting C&W generation.
  • To improve the accuracy and reliability of C&W generation predictions for better disposal planning and policymaking.

Main Methods:

  • Transformation of the initial sequence and incorporation of the three-parameter interval grey number to handle data issues.
  • Integration of the three-parameter interval grey number with waste generation coefficients for precise C&W range determination.
  • Optimization of the time lag coefficient using the COOT algorithm to enhance prediction accuracy.

Main Results:

  • The enhanced grey model demonstrates superior performance compared to traditional grey prediction and exponential smoothing methods.
  • The model provides a more accurate and reliable range for C&W generation prediction.
  • Case study in Guangzhou validates the model's effectiveness and applicability.

Conclusions:

  • The novel forecasting method provides a scientific foundation for regional construction waste treatment, disposal, and resource allocation.
  • The study offers crucial reference values for C&W disposal planning and policymaking.
  • The enhanced grey model offers a rational, applicable, and effective solution for C&W management.