Skip to main content

Advertisement

SpringerLink
Log in

Decision-making model based vertical transportation channel for super high-rise construction waste

  • Published:
Cluster Computing Aims and scope Submit manuscript

Abstract

With the rapid acceleration of urbanization and incessant enhancement of social productivity, high-rise buildings more than 100 m heights are more and more popular in our country. The construction stage is the important segment of pollution and energy consumption in the whole process of engineering construction. The vertical transportation and recycling of construction waste has had a huge impact on high-rise buildings’ construction and management, but the domestic researches on these aspects are insufficient. In this paper, PLS–LSSVM model is employed to predict the construction waste in allusion to problems of construction waste vertical transportation. And then we put forward the feasible construction waste vertical transportation scheme, and design the construction waste transport corridor and the implementation of vacuum recycling devices. The implementation plan realizes the repeated recycling of construction waste, improves transmission efficiency, and reduce environmental pollution, which will alleviate the pressure of high-rise buildings’ vertical transportation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Abbreviations

\(F_{0} \) :

Standardization matrix of the dependent variable Y

\(E_{0} \) :

Standardization matrix of the independent variable set X

\(p_{1} \) :

Regression coefficient of \(E_{0} \) to \(t_{1} \)

\(E_{1} \) :

Residual error matrix of regression equation \(E_{1} =E_{0} {-t_{1} p_{1}}^{T} \)

\(X_{i} \in {R}^d\) :

d dimension training sample input data

\(y_{i} \in R\) :

Training sample output data

\(\omega \) :

Weight vector

\(\varphi (\cdot )\) :

Nonlinear mapping function

\(\gamma \) :

Negative constant

\(\xi \) :

Relaxation factor

b :

Threshold. Use Lagrange method to solve the above problem

\(\alpha _{i} \) :

Lagrange multiplier

I :

Unit column

E :

Unit matrix of \(N\times N\)

\(y_{i} \) :

Actual value of sample

\(\hat{{y}}_{i} \) :

LS-SVM regression function estimates that given patterns

N :

Number of samples

\(a_{ij} \) :

Value of relative important degree of any two factors in a certain level A is obtained from experts

References

  1. Lu, W., Peng, Y., Webster, C., et al.: Stakeholders’ willingness to pay for enhanced construction waste management: a Hong Kong study. Renew. Sustain. Energy Rev. 47, 233–240 (2015)

    Article  Google Scholar 

  2. Mendis, D., Hewage, K.N., Wrzesniewski, J.: Contractual obligations analysis for construction waste management in Canada. J. Civ. Eng. Manag. 21(7), 866–880 (2015)

    Article  Google Scholar 

  3. Oviedo, G.A.M., Gutiérrez, M.A.P., Luna, Y.H.D.: Construction waste disposal zone as an alternative for erosion control on urbanized plateaus. ESAICA 2(1), 43–55 (2016)

    Google Scholar 

  4. Yeheyis, M., Hewage, K., Alam, M.S., et al.: An overview of construction and demolition waste management in Canada: a lifecycle analysis approach to sustainability. Clean Technol. Environ. Policy 15(1), 81–91 (2013)

    Article  Google Scholar 

  5. Fan, F., Wang, H., Zhi, X., et al.: Investigation of construction vertical deformation and pre-deformation control for three super high-rise buildings. Adv. Struct. Eng. 1611, 1885–1898 (2013)

    Article  Google Scholar 

  6. Joh, H.W., Lim, I.S., Choi, Y.H., et al.: A new construction process in core wall of high-rise building: core structure succeeding method. Adv. Mater. Res. 838, 241–244 (2014)

    Google Scholar 

  7. Balakrishnan, K., Olutoye, M.A., Hameed, B.H.: Synthesis of methyl esters from waste cooking oil using construction waste material as solid base catalyst. Bioresour. Technol. 128, 788–791 (2013)

    Article  Google Scholar 

  8. Ju, F., Ju, F., Zhang, Q.: Vertical transportation system of solid material for backfilling coal mining technology. Int. J. Min. Sci. Technol. 22, 41–45 (2012)

    Article  Google Scholar 

  9. Kim, E.S., Choi, S.K.: Failure analysis of connecting bolts in collapsed tower crane. Fatigue Fract. Eng. Mater. Struct. 363, 228–241 (2012)

    Google Scholar 

  10. Weiblen, J., Zerelles, H.: Shaft climber: high-performance construction elevator for high-rise buildings. ThyssenKrupp techforum 1, 31–33 (2014)

    Google Scholar 

  11. Ren, W., Yunxin, W., Zhang, Z.: A dynamic model of mobile concrete pump boom based on discrete time transfer matrix method. Front. Mech. Eng. 84, 360–366 (2013)

    Article  Google Scholar 

  12. Wu, Z., Ann, T.W., Shen, L., et al.: Quantifying construction and demolition waste: an analytical review. Waste Manag. 34(9), 1683–1692 (2014)

    Article  Google Scholar 

  13. Poon, C.S., Yu, A.T.W., Wong, A., et al.: Quantifying the impact of construction waste charging scheme on construction waste management in Hong Kong. J. Constr. Eng. Manag. 139(5), 466–479 (2013)

    Article  Google Scholar 

  14. Yuan, H., Lu, W., Hao, J.J.: The evolution of construction waste sorting on-site. Renew. Sustain. Energy Rev. 20, 483–490 (2013)

    Article  Google Scholar 

  15. Moretti, J.P., Sales, A., Almeida, F.C.R., et al.: Joint use of construction waste (CW) and sugarcane bagasse ash sand (SBAS) in concrete. Constr. Build. Mater. 113, 317–323 (2016)

    Article  Google Scholar 

  16. Mália, M., de Brito, J., Pinheiro, M.D., et al.: Construction and demolition waste indicators. Waste Manag. Res. 31(3), 241–255 (2013)

    Article  Google Scholar 

  17. Kern, A.P., Dias, M.F., Kulakowski, M.P., et al.: Waste generated in high-rise buildings construction: a quantification model based on statistical multiple regression. Waste Manag. 39, 35–44 (2015)

    Article  Google Scholar 

  18. Lachimpadi, S.K., Pereira, J.J., Taha, M.R., et al.: Construction waste minimisation comparing conventional and precast construction (Mixed System and IBS) methods in high-rise buildings: a Malaysia case study. Resour. Conserv. Recycl. 68, 96–103 (2012)

    Article  Google Scholar 

  19. Chiveralls, K., Palmer, J., Pullen, S., et al.: Stakeholder perspectives on waste in construction: global change, contextual issues and industry culture. AUBEA and Unitec (2013)

  20. Tam, V.W.Y., Lu, W.: Construction waste management profiles, practices, and performance: a cross-jurisdictional analysis in four countries. Sustainability 8(2), 190 (2016)

    Article  Google Scholar 

  21. Bagdi, N., Aggarwal, V., Sherwal, N.: Management of construction waste in India: a case of green technology. Glob. J. Manag. Bus. Stud. 3(4), 361–364 (2013)

    Google Scholar 

  22. Holmes, S.J., Osmani, M.: Planning for waste management. In: A Handbook for Construction Planning and Scheduling, pp. 216–227 (2014)

  23. Lu, W., Yuan, H.: Off-site sorting of construction waste: what can we learn from Hong Kong? Resour. Conserv. Recycl. 69, 100–108 (2012)

    Article  Google Scholar 

  24. Cha, N., Park, W., Kim, K., et al.: Construction waste management system for improving waste treatment on the construction site. Korean J. Constr. Eng. Manag. 15(3), 83–91 (2014)

    Article  Google Scholar 

  25. Li, R.Y.M., Du, H.: Sustainable construction waste management in Australia: a motivation perspective.//Construction Safety and Waste Management. Springer International Publishing, New York, pp. 1–30 (2015)

  26. Lin, M.I.B., Groves, W.A., Freivalds, A., Lee, E.G., Harper, M.: Comparison of artificial neural network (ANN) and partial least squares (PLS) regression models for predicting respiratory ventilation: an exploratory study. Eur. J. Appl. Physiol. 1125, 1603–1611 (2012)

    Article  Google Scholar 

  27. Afantitis, A., Melagraki, G., Sarimveis, H., Koutentis, P.A.: A combined LS-SVM & MLR QSAR workflow for predicting the inhibition of CXCR3 receptor by quinazolinone analogs. Mol. Divers. 142, 225–235 (2010)

    Article  Google Scholar 

  28. Kokangül, A., Polat, U., Dağsuyu, C.: A new approximation for risk assessment using the AHP and Fine Kinney methodologies. Saf. Sci., 134–139 (2016)

  29. Xu, Z., Mei, L., Hu, C., Liu, Y.: The big data analytics and applications of the surveillance system using video structured description technology. Clust. Comput. 19(3), 1283–1292 (2016)

    Article  Google Scholar 

  30. Xu, Z., Zhang, H., Hu, C., Mei, L., Xuan, J., Choo, K.R., Sugumaran, V., Zhu, Y.: Building knowledge base of urban emergency events based on crowdsourcing of social media. Concurr. Comput.: Pract. Exp. 28(15), 4038–4052 (2016)

    Article  Google Scholar 

  31. Xu, Z., Zhang, H., Sugumaran, V., Choo, K.R., Mei, L., Zhu, Y.: Participatory sensing-based semantic and spatial analysis of urban emergency events using mobile social media. EURASIP J. Wireless Commun. Netw. 2016, 44 (2016)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Civil Engineering, Wuhan University, Wuhan, 430072, China

    Lin Yang, YaBo He, Yichen Li & Mengping Zhang

Authors
  1. Lin Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. YaBo He
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yichen Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mengping Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Lin Yang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yang, L., He, Y., Li, Y. et al. Decision-making model based vertical transportation channel for super high-rise construction waste. Cluster Comput 20, 253–262 (2017). https://doi.org/10.1007/s10586-016-0679-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10586-016-0679-1

Keywords

Search

Navigation