Open Access
E3S Web Conf.
Volume 202, 2020
The 5th International Conference on Energy, Environmental and Information System (ICENIS 2020)
Article Number 06003
Number of page(s) 13
Section Green Infrastructure and Resilience
Published online 10 November 2020
  1. Y. Shao, Q. Jiang, C. Wang, M. Wang, L. Xiao, and Y. Qi, ―Analysis of critical land degradation and development processes and their driving mechanism in the Heihe River Basin,ǁ Sci. Total Environ., vol. 716, p. 137082, 2020, doi: 10.1016/j.scitotenv.(2020).137082. [CrossRef] [Google Scholar]
  2. D. Patrman, A. Splichalova, D. Rehak, and V. Onderkova, ―Factors influencing the performance of critical land transport infrastructure elements,ǁ Transp. Res. Procedia, vol. 40, pp. 1518–1524, (2019), doi: 10.1016/j.trpro.2019.07.210. [Google Scholar]
  3. M. Rajasekhar, G. Sudarsana Raju, Y. Sreenivasulu, and R. Siddi Raju, ―Delineation of groundwater potential zones in semi-arid region of Jilledubanderu river basin, Anantapur District, Andhra Pradesh, India using fuzzy logic, AHP and integrated fuzzy-AHP approaches,ǁ HydroResearch, vol. 2, pp. 97–108, (2019), doi: 10.1016/j.hydres.2019.11.006. [Google Scholar]
  4. A. E. Wolnowska and W. Konicki, ― Multi-criterial analysis of oversize cargo transport through the city, using the AHP method,ǁ Transp. Res. Procedia, vol. 39, no. 2018, pp. 614–623, (2019), doi: 10.1016/j.trpro.2019.06.063. [Google Scholar]
  5. E. Lima, E. Gorski, E. F. R. Loures, E. A. Portela Santos, and F. Deschamps, ―Applying machine learning to AHP multicriteria decision making method to assets prioritization in the context of industrial maintenance 4.0,ǁ IFAC-PapersOnLine, vol. 52, no. 13, pp. 2152–2157, (2019), doi: 10.1016/j.ifacol.2019.11.524. [Google Scholar]
  6. F. Moussaoui, M. Cherrared, M. A. Kacimi, and R. Belarbi, ―A genetic algorithm to optimize consistency ratio in AHP method for energy performance assessment of residential buildings—Application of top-down and bottom-up approaches in Algerian case study,ǁ Sustain. Cities Soc., vol. 42, pp. 622–636, (2018), doi: 10.1016/j.scs.2017.08.008. [CrossRef] [Google Scholar]
  7. A. Calabrese, R. Costa, N. Levialdi, and T. Menichini, ―Integrating sustainability into strategic decision-making: A fuzzy AHP method for the selection of relevant sustainability issues,ǁ Technol. Forecast. Soc. Change, vol. 139, no. March, pp. 155–168, (2019), doi: 10.1016/j.techfore.2018.11.005. [CrossRef] [Google Scholar]
  8. C. Ulloa, J. M. Nuñez, C. Lin, and G. Rey, ― AHP-based design method of a lightweight, portable and flexible air-based PV-T module for UAV shelter hangars,ǁ Renew. Energy, vol. 123, pp. 767–780, (2018), doi: 10.1016/j.renene.2018.02.099. [Google Scholar]
  9. M. Khalili, K. Jadidi, M. Karakouzian, and S. Amirkhanian, ― Rheological properties of modified crumb rubber asphalt binder and selecting the best modified binder using AHP method,ǁ Case Stud. Constr. Mater., vol. 11, p. e00276, (2019), doi: 10.1016/j.cscm.2019.e00276. [Google Scholar]
  10. B. Tashayo, A. Honarbakhsh, M. Akbari, and M. Eftekhari, —Land suitability assessment for maize farming using a GIS-AHP method for a semi- arid region, Iran,! J. Saudi Soc. Agric. Sci., no. xxxx, (2020), doi: 10.1016/j.jssas.2020.03.003. [Google Scholar]
  11. M. Kim, Y.C. Jang, and S. Lee, —Application of Delphi-AHP methods to select the priorities of WEEE for recycling in a waste management decision-making tool,! J.Environ. Manage., vol. 128, pp. 941-948, (2013),doi:10.1016/j.jenvman.2013.06.049. [CrossRef] [Google Scholar]
  12. C. Ren, Z. Li, and H. Zhang, —Integrated multi-objective stochastic fuzzy programming and AHP method for agricultural water and land optimization allocation under multiple uncertainties,II J. Clean. Prod., vol. 210, pp. 12-24, (2019), doi: 10.1016/j.jclepro.2018.10.348. [Google Scholar]
  13. I. A§chilean, G. Badea, I. Giurca, G. S. Naghiu, and F. G. Iloaie, —Choosing the Optimal Technology to Rehabilitate the Pipes in Water Distribution Systems Using the AHP Method,! Energy Procedia, vol. 112, no. October 2016, pp. 19-26, (2017), doi: 10.1016/j.egypro.2017.03.1109. [Google Scholar]
  14. P. Chen, —Effects of normalization on the entropy-based TOPSIS method,! Expert Syst. Appl., vol. 136, pp. 33-41, (2019), doi: 10.1016/j.eswa.2019.06.035. [Google Scholar]
  15. X. Ye, Y. Kang, Z. Yan, B. Chen, and K. Zhong, —Optimization study of return vent height for an impinging jet ventilation system with exhaust/return-split configuration by TOPSIS method,! Build. Environ., vol. 177, no. April, p. 106858, (2020), doi: 10.1016/j.buildenv.2020.106858. [Google Scholar]
  16. R. F. de F. Aires and L. Ferreira, —A new approach to avoid rank reversal cases in the TOPSIS method,! Comput. Ind. Eng., vol. 132, no. April, pp. 84-97, (2019), doi: 10.1016/j.cie.2019.04.023. [Google Scholar]
  17. S. Yousefzadeh, K. Yaghmaeian, A. H. Mahvi, S. Nasseri, N. Alavi, and R. Nabizadeh, —Comparative analysis of hydrometallurgical methods for the recovery of Cu from circuit boards: Optimization using response surface and selection of the best technique by two-step fuzzy AHP-TOPSIS method,! J. Clean. Prod., vol. 249, p. 119401, (2020), doi: 10.1016/j.jclepro.2019.119401. [Google Scholar]

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