Using Fuzzy Cognitive Maps For Modeling Environmental Aspect of Sustainable Development in Construction Projects
DOI:
https://doi.org/10.37385/jaets.v7i1.7041Keywords:
Fuzzy Cognitive Map, Sustainable Development, Static Analysis, Dynamic Analysis, Relative Importance IndexAbstract
The pillars of sustainable development are representing the interface between environmental, economic, and social sustainability. Sustainable development is a method of planning and managing construction projects to reduce the effect of the construction process on the environment so that there is a balance between environmental capabilities and the human needs of present and future generations. Usually, Environmental sustainability is most important and effective in construction projects. The environment suffers from significant negative impacts as a result of the implementation of construction projects; therefore, this study aims to identify the effecting factors on environmentally sustainable development. The methodology of this study used fuzzy cognitive maps (FCMs) because of adopted simulation approach, after selecting the factors that have RII more than 65% and determine causal relationship between factors by applying fuzzy logic using MATLAB program. Then the effecting factors were analyzed and ranked by static and dynamic analysis. The results showed the static analysis of effecting factors on ESD in first quarter are characterized by influential and affected by other factors of (ESD), were include (C2.4, C4.6, C1.6, C2.1, C3.3, C3.7, C3.6, C6.2), When comparing between dynamic analysis and RII of the factors, it has been noticed a difference in the importance. This is an essential finding in the understanding that dynamic analysis considers the interactions between factors, while the RII takes the reasons independently and neglects interactions between them. The study has provided recommendations for the application of (FCM) model that was proposed depend on these factors in building projects to improve the environment and reduce its negative effects.
Downloads
References
Abdel-Basset, M., Gamal, A., Chakrabortty, R. K., Ryan, M., & El-Saber, N. (2021). A comprehensive framework for evaluating sustainable green building indicators under an uncertain environment. Sustainability, 13(11), 6243. https://doi.org/10.1109/ 10.3390/su13116243
Alhilli, H. K., & Rezoqi, S. I. (2021). Investigating variation orders causes in Iraqi building construction projects. In E3S Web of Conferences (Vol. 318, p. 02003). EDP Sciences. https://doi.org/10.1109/10.1051/e3sconf/202131802003
Alola, A. A., Özkan, O., & Usman, O. (2023). Role of non-renewable energy efficiency and renewable energy in driving environmental sustainability in India: evidence from the load capacity factor hypothesis. Energies, 16(6), 2847. https://doi.org/10.1109/10.3390/en16062847
Bhutani, K., & Kumar, M. (2015, March). Fuzzy inference system & fuzzy cognitive maps based classification. In 2015 International Conference on Advances in Computer Engineering and Applications (pp. 305-309). IEEE. https://doi.org/10.1109/10.1109/ICACEA.2015.7164720
Datta, S. D., Tayeh, B. A., Hakeem, I. Y., & Abu Aisheh, Y. I. (2023). Benefits and barriers of implementing building information modeling techniques for sustainable practices in the construction industry—A comprehensive review. Sustainability, 15(16), 12466. https://doi.org/10.1109/10.3390/su151612466
Dzhidzhelava, D., & Fedina, A. (2020). The environmental component of construction projects in the aspect of sustainable development. IOP Conference Series: Materials Science and Engineering. https://doi.org/10.1109/10.1088/1757-899X/890/1/012178
Feroz, A. K., Zo, H., & Chiravuri, A. (2021). Digital transformation and environmental sustainability: A review and research agenda. Sustainability, 13(3), 1530. https://doi.org/10.1109/10.3390/su13031530
Fokaides, P. A., Apanaviciene, R., Cerneckiene, J., Jurelionis, A., Klumbyte, E., Kriauciunaite-Neklejonoviene, V., Pupeikis, D., Rekus, D., Sadauskiene, J., & Seduikyte, L. (2020). Research challenges and advancements in the field of sustainable energy technologies in the built environment. Sustainability, 12(20), 8417. https://doi.org/10.1109/10.3390/su12208417
Furfaro, R., Kargel, J. S., Lunine, J. I., Fink, W., & Bishop, M. P. (2010). Identification of cryovolcanism on Titan using fuzzy cognitive maps. Planetary and Space Science, 58(5), 761-779. https://doi.org/10.1109/10.1016/j.pss.2009.12.003
Gayen, D., Chatterjee, R., & Roy, S. (2024). A review on environmental impacts of renewable energy for sustainable development. International Journal of Environmental Science and Technology, 21(5), 5285-5310. https://doi.org/10.1109/10.1007/s13762-023-05380-z
Horzela-Mis, A., & Semrau, J. (2025). The role of renewable energy and storage technologies in sustainable development: simulation in the construction industry. Frontiers in Energy Research, 13, 1540423. https://doi.org/10.1109/10.3389/fenrg.2025.1540423
Jahantigh, F. F., Khanmohammadi, E., & Sarafrazi, A. (2018). Crisis management model using fuzzy cognitive map. International Journal of Business Excellence, 16(2), 177-198. https://doi.org/10.1109/10.1504/IJBEX.2018.10015930
Jarkas, A. M., & Mubarak, S. A. (2016). Causes of construction change orders in Qatar: contractors' perspective. International Journal of Project Organisation and Management, 8(3), 275-299. https://doi.org/10.1109/10.1504/IJPOM.2016.078273
Jiya, E. A., & Georgina, O. N. (2023). A review of fuzzy cognitive maps extensions and learning. Journal of Information Systems and Informatics, 5(1), 300-323. https://doi.org/10.1109/10.51519/journalisi.v5i1.447
Kasayanond, A., Umam, R., & Jermsittiparsert, K. (2019). Environmental sustainability and its growth in Malaysia by elaborating the green economy and environmental efficiency. International Journal of Energy Economics and Policy, 9(5), 465-473. https://doi.org/10.1109/10.32479/ijeep.8310
Khanzadi, M., Nasirzadeh, F., & Dashti, M. S. (2018). Fuzzy cognitive map approach to analyze causes of change orders in construction projects. Journal of Construction Engineering and Management, 144(2), 04017111. https://doi.org/10.1109/10.1061/(ASCE)CO.1943-7862.0001430
Kiani Mavi, R., Gengatharen, D., Kiani Mavi, N., Hughes, R., Campbell, A., & Yates, R. (2021). Sustainability in construction projects: a systematic literature review. Sustainability, 13(4), 1932. https://doi.org/10.1109/10.3390/su13041932
Leibovich-Raveh, T., Lewis, D. J., Kadhim, S. A.-R., & Ansari, D. (2018). A new method for calculating individual subitizing ranges. Journal of Numerical Cognition, 4(2), 429-447. https://doi.org/10.1109/10.5964/jnc.v4i2.74
Napoles, G., Espinosa, M. L., Grau, I., & Vanhoof, K. (2018). FCM expert: software tool for scenario analysis and pattern classification based on fuzzy cognitive maps. International Journal on Artificial Intelligence Tools, 27(07), 1860010. https://doi.org/10.1109/10.1142/S0218213018600102
Nasirzadeh, F., Ghayoumian, M., Khanzadi, M., & Rostamnezhad Cherati, M. (2020). Modelling the social dimension of sustainable development using fuzzy cognitive maps. International journal of construction management, 20(3), 223-236. https://doi.org/10.1109/10.1080/15623599.2018.1484847
Onubi, H. O., Yusof, N. A., & Hasan, A. S. (2020). Effects of sustainable construction site practices on environmental performance of construction projects in Nigeria. Planning Malaysia, 18. https://doi.org/10.1109/10.21837/pm.v18i11.710
Orieno, O. H., Ndubuisi, N. L., Eyo-Udo, N. L., Ilojianya, V. I., & Biu, P. W. (2024). Sustainability in project management: A comprehensive review. World Journal of Advanced Research and Reviews, 21(1), 656-677. https://doi.org/10.1109/10.30574/wjarr.2024.21.1.0060
Papakostas, G. A., Koulouriotis, D. E., Polydoros, A. S., & Tourassis, V. D. (2012). Towards Hebbian learning of fuzzy cognitive maps in pattern classification problems. Expert Systems with Applications, 39(12), 10620-10629. https://doi.org/10.1109/10.1016/j.eswa.2012.02.148
Patro, S. (2015). Normalization: A preprocessing stage. arXiv preprint arXiv:1503.06462.
Stylios, C. D., & Groumpos, P. P. (1998). The challenge of modelling supervisory systems using fuzzy cognitive maps. Journal of Intelligent Manufacturing, 9, 339-345. https://doi.org/10.1109/10.1023/A:1008978809938
Uralovich, K. S., Toshmamatovich, T. U., Kubayevich, K. F., Sapaev, I., Saylaubaevna, S. S., Beknazarova, Z., & Khurramov, A. (2023). A primary factor in sustainable development and environmental sustainability is environmental education. Caspian Journal of Environmental Sciences, 21(4), 965-975. https://doi.org/10.1109/10.22124/CJES.2023.7104
Winanda, L. A. R., Yami, N., Kartika, D., Manaha, Y. P., & Ma’ruf, A. (2024). Achieving Green Construction Rating in Building Projects with Fuzzy System Approach. In E3S Web of Conferences (Vol. 476, p. 01024). EDP Sciences. https://doi.org/10.1109/10.1051/e3sconf/202447601024
Yoon, B. S., & Jetter, A. J. (2016, September). Comparative analysis for fuzzy cognitive mapping. In 2016 Portland International Conference on Management of Engineering and Technology (PICMET) (pp. 1897-1908). IEEE. https://doi.org/10.1109/PICMET.2016.7806755
CITEDNESS IN SCOPUS
CITEDNESS IN WOS
