Developing a comprehensive risk assessment model based on fuzzy Bayesian belief network (FBBN)
Abstract
Reliable and efficient risk assessments are essential to deal effectively with potential risks in international construction projects. However, most conventional risk modeling methods are based on the hypothesis that risk factors are independent, which does not account adequately for the causal relationships among risk factors. In this study, a risk assessment model for international construction projects was developed to improve the efficacy of risk management by integrating fault tree analysis and fuzzy set theory with a Bayesian belief network. The risk rating of each risk factor, expressed as the product of risk occurrence probability and impact, was incorporated into the risk assessment model to evaluate degrees of risk. Therefore, risk factors were categorized into different risk levels taking into account their inherent causal relationships, which allowed the identification of critical risk factors. The applicability of the fuzzy Bayesian belief network-based risk assessment model was verified using a case study through a comparative analysis with the results from a fuzzy synthetic evaluation method. The comparison shows that the proposed risk assessment model is able to provide guidelines for an effective risk management process and ultimately to increase project performance in a complex environment such as international construction projects.
Keyword : international construction projects, risk assessment, causal relationships, fuzzy numbers, fuzzy Bayesian belief network, fault tree analysis, fuzzy synthetic evaluation
How to Cite
Guan, L., Liu, Q., Abbasi, A., & Ryan, M. J. (2020). Developing a comprehensive risk assessment model based on fuzzy Bayesian belief network (FBBN). Journal of Civil Engineering and Management, 26(7), 614-634. https://doi.org/10.3846/jcem.2020.12322
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Abdelgawad, M., & Fayek, A. R. (2012). Comprehensive hybrid framework for risk analysis in the construction industry using combined failure mode and effect analysis, fault trees, event trees, and fuzzy logic. Journal of Construction Engineering and Management, 138(5), 642–651. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000471
Abdollahzadeh, G., & Rastgoo, S. (2015). Risk assessment in bridge construction projects using fault tree and event tree analysis methods based on fuzzy logic. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 1(3), 031006. https://doi.org/10.1115/1.4030779
Andrić, J. M., & Lu, D. J. (2016). Risk assessment of bridges under multiple hazards in operation period. Safety Science, 83, 80–92. https://doi.org/10.1016/j.ssci.2015.11.001
Bobbio, A., Portinale, L., Minichino, M., & Ciancamerla, E. (2001). Improving the analysis of dependable systems by mapping fault trees into Bayesian networks. Reliability Engineering and System Safety, 71(3), 249–260. https://doi.org/10.1016/S0951-8320(00)00077-6
Bu-Qammaz, A. S., Dikmen, I., & Birgonul, M. T. (2009). Risk assessment of international construction projects using the analytic network process. Canadian Journal of Civil Engineering, 36(7), 1170–1181. https://doi.org/10.1139/L09-061
Cárdenas, I. C., Al-Jibouri, S. S., Halman, J. I., & van Tol, F. A. (2013). Modeling risk-related knowledge in tunneling projects. Risk Analysis, 34(2), 323–339. https://doi.org/10.1111/risa.12094
Chen, S. M., Munif, A., Chen, G. S., Liu, H. C., & Kuo, B. C. (2012). Fuzzy risk analysis based on ranking generalized fuzzy numbers with different left heights and right heights. Expert Systems with Applications, 39(7), 6320–6334. https://doi.org/10.1016/j.eswa.2011.12.004
Chen, T.-T., & Wang, C.-H. (2017). Fall risk assessment of bridge construction using Bayesian network transferring from fault tree analysis. Journal of Civil Engineering and Management, 23(2), 273–282. https://doi.org/10.3846/13923730.2015.1068841
Cheng, M., & Lu, Y. (2015). Developing a risk assessment method for complex pipe jacking construction projects. Automation in Construction, 58, 48–59. https://doi.org/10.1016/j.autcon.2015.07.011
Chien, K.-F., Wu, Z.-H., & Huang, S.-C. (2014). Identifying and assessing critical risk factors for BIM projects: Empirical study. Automation in Construction, 45, 1–15. https://doi.org/10.1016/j.autcon.2014.04.012
Deng, X., Pheng, L. S., & Zhao, X. (2014). Project system vulnerability to political risks in international construction projects: The case study of Chinese contractors. Project Management Journal, 45(2), 20–33. https://doi.org/10.1002/pmj.21397
El-Sayegh, S. M. (2008). Risk assessment and allocation in the UAE construction industry. International Journal of Project Management, 26(4), 431–438. https://doi.org/10.1016/j.ijproman.2007.07.004
Guo, C., Khan, F., & Imtiaz, S. (2019). Copula-based Bayesian network model for process system risk assessment. Process Safety and Environment Protection, 123, 317–326. https://doi.org/10.1016/j.psep.2019.01.022
Hu, Y., Zhang, X., Ngai, E. W. T., Cai, R., & Liu, M. (2013). Software project risk analysis using Bayesian networks with causality constraints. Decision Support Systems, 56, 439–449. https://doi.org/10.1016/j.dss.2012.11.001
Islam, M. S., Nepal, M. P., Skitmore, M., & Attarzadeh, M. (2017). Current research trends and application areas of fuzzy and hybrid methods to the risk assessment of construction projects. Advanced Engineering Informatics, 33, 112–131. https://doi.org/10.1016/j.aei.2017.06.001
John, A., Paraskevadakis, D., Bury, A., Yang, Z., Riahi, R., & Wang, J. (2014). An integrated fuzzy risk assessment for seaport operations. Safety Science, 68, 180–194. https://doi.org/10.1016/j.ssci.2014.04.001
John, A., Yang, Z., Riahi, R., & Wang, J. (2016). A risk assessment approach to improve the resilience of a seaport system using Bayesian networks. Ocean Engineering, 111, 136–147. https://doi.org/10.1016/j.oceaneng.2015.10.048
Kabir, G., Sadiq, R., & Tesfamariam, S. (2016). A fuzzy Bayesian belief network for safety assessment of oil and gas pipelines. Structure and Infrastructure Engineering, 12(8), 874–889. https://doi.org/10.1080/15732479.2015.1053093
Khakzad, N., Khan, F., & Amyotte, P. (2011). Safety analysis in process facilities: Comparison of fault tree and Bayesian network approaches. Reliability Engineering and System Safety, 96(8), 925–932. https://doi.org/10.1016/j.ress.2011.03.012
Khanzadi, M., Eshtehardian, E., & Mokhlespour Esfahani, M. (2017). Cash flow forecasting with risk consideration using Bayesian belief networks (BBNS). Journal of Civil Engineering and Management, 23(8), 1045–1059. https://doi.org/10.3846/13923730.2017.1374303
Khodakarami, V., & Abdi, A. (2014). Project cost risk analysis: A Bayesian networks approach for modeling dependences between cost items. International Journal of Project Management, 32(7), 1233–1245. https://doi.org/10.1016/j.ijproman.2014.01.001
Kuo, Y. C., & Lu, S. T. (2013). Using fuzzy multiple criteria decision making approach to enhance risk assessment for metropolitan construction projects. International Journal of Project Management, 31(4), 602–614. https://doi.org/10.1016/j.ijproman.2012.10.003
Leu, S. S., & Chang, C. M. (2013). Bayesian-network-based safety risk assessment for steel construction projects. Accidents Analysis and Prevention, 54, 122–133. https://doi.org/10.1016/j.aap.2013.02.019
Li, P., Chen, G., Dai, L., & Zhang, L. (2012). A fuzzy Bayesian network approach to improve the qualification of organizational influences in HRA frameworks. Safety Science, 50(7), 1569–1583. https://doi.org/10.1016/j.ssci.2012.03.017
Liu, J., Zhao, X., & Yan, P. (2016). Risk paths in international construction projects: case study from Chinese contractors. Journal of Construction Engineering and Management, 142(6), 05016002. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001116
Luu, V. T., Kim, S. Y., Tuan, N. V., & Qgunlana, S. O. (2009). Quantifying schedule risk in construction projects using Bayesian belief networks. International Journal of Project Management, 27(1), 39–50. https://doi.org/10.1016/j.ijproman.2008.03.003
Meng, X., Chen, G., Zhu, G., & Zhu, Y. (2019). Dynamic quantitative risk assessment of accidents induced by leakage on offshore platforms using DEMATEL-BN. International Journal of Naval Architecture and Ocean Engineering, 11(1), 22–32. https://doi.org/10.1016/j.ijnaoe.2017.12.001
Ojha, R., Ghadge, A., Tiwari, M. K., & Bititci, U. S. (2018). Bayesian network modelling for supply chain risk propagation. International Journal of Production Research, 56(17), 5795–5819. https://doi.org/10.1080/00207543.2018.1467059
Qazi, A., & Dikmen, I. (2019). From risk matrices to risk networks in construction projects. IEEE Transactions on Engineering Management (early access). https://doi.org/10.1109/TEM.2019.2907787
Qazi, A., Dickson, A., Quigley, J., & Gaudenzi, B. (2018). Supply chain risk network management: A Bayesian belief network and expected utility based approach for managing supply chain risks. International Journal of Production Economics, 196, 24–42. https://doi.org/10.1016/j.ijpe.2017.11.008
Rao, P. P. B., & Shankar, N. R. (2011). Ranking fuzzy numbers with a distance method using circumcenter of centroids and an index of modality. Advances in Fuzzy Systems, 178308. https://doi.org/10.1155/2011/178308
Ren, J., Jenkinson, I., Wang, J., Xu, D. L., & Yang, J. B. (2009). An offshore risk analysis method using fuzzy Bayesian network. Journal of Offshore Mechanics and Arctic Engineering, 131(4), 041101. https://doi.org/10.1115/1.3124123
Ross, T. J. (2004). Fuzzy logic with engineering applications (2nd ed.). Wiley.
Samantra, C., Datta, S., & Mahapatra, S. S. (2017). Fuzzy based risk assessment module for metropolitan construction project: An empirical study. Engineering Applications of Artificial Intelligence, 65, 449–464. https://doi.org/10.1016/j.engappai.2017.04.019
Seker, S., & Zavadskas, E. K. (2017). Application of fuzzy DEMATEL method for analyzing occupational risks on construction sites. Sustainability, 9(11), 2083. https://doi.org/10.3390/su9112083
Taylan, O., Bafail, A. O., Abdulaal, R. M. S., & Kabli, M. R. (2014). Construction projects selection and risk assessment by fuzzy AHP and fuzzy TOPSIS methodologies. Applied Soft Computing, 17, 105–116. https://doi.org/10.1016/j.asoc.2014.01.003
Valipour, A., Yahaya, N., Md Noor, N., Antuchevičienė, J., & Tamošaitienė, J. (2017). Hybrid SWARA-COPRAS method for risk assessment in deep foundation excavation project: An Iranian case study. Journal of Civil Engineering and Management, 23(4), 524–532. https://doi.org/10.3846/13923730.2017.1281842
Wang, T., Wang, S., Zhang, L., Huang, Z., & Li, Y. (2016). A major infrastructure risk-assessment framework: Application to a cross-sea route project in China. International Journal of Project Management, 34(7), 1403–1415. https://doi.org/10.1016/j.ijproman.2015.12.006
Wang, Z. Z., & Chen, C. (2017). Fuzzy comprehensive Bayesian network-based safety risk assessment for metro construction projects. Tunnelling and Underground Space Technology, 70, 330–342. https://doi.org/10.1016/j.tust.2017.09.012
Weber, P., Medina-Oliva, G., Simon, C., & Iung, B. (2012). Overview on Bayesian networks applications for dependability, risk analysis and maintenance areas. Engineering Applications of Artificial Intelligence, 25(4), 671–682. https://doi.org/10.1016/j.engappai.2010.06.002
Wilson, A. G., & Huzurbazar, A. V. (2007). Bayesian networks for multilevel system reliability. Reliability Engineering and System Safety, 92(10), 1413–1420. https://doi.org/10.1016/j.ress.2006.09.003
Wu, Y., Li, L., Xu, R., Chen, K., Hu, Y., & Lin, X. (2017). Risk assessment in straw-based power generation public-private partnership projects in China: A fuzzy synthetic evaluation analysis. Journal of Cleaner Production, 161, 977–990. https://doi.org/10.1016/j.jclepro.2017.06.008
Xu, Y., Yeung, J. F. Y., Chan, A. P. C., Chan, D. W. M., Wang, S. Q., & Ke, Y. (2010). Developing a risk assessment model for PPP projects in China–A fuzzy synthetic evaluation approach. Automation in Construction, 19(7), 929–943. https://doi.org/10.1016/j.autcon.2010.06.006
Yazdi, M., & Kabir, S. (2017). A fuzzy Bayesian network approach for risk analysis in process industries. Process Safety and Environmental Protection, 111, 507–519. https://doi.org/10.1016/j.psep.2017.08.015
Yildiz, A. E., Dikmen, I., Birgonul, M. T., Ercoskun, K., & Alten, S. (2014). A knowledge-based risk mapping tool for cost estimation of international construction projects. Automation in Construction, 43, 144–155. https://doi.org/10.1016/j.autcon.2014.03.010
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X
Zarei, E., Khakzad, N., Cozzani, V., & Reniers, G. (2019). Safety analysis of process systems using Fuzzy Bayesian Network (FBN). Journal of Loss Prevention in the Process Industries, 57, 7–16. https://doi.org/10.1016/j.jlp.2018.10.011
Zavadskas, E. K., Turskis, Z., & Tamosaitiene, J. (2010). Risk Assessment of Construction Projects. Journal of Civil Engineering and Management, 16(1), 33–46. https://doi.org/10.3846/jcem.2010.03
Zhang, L., Wu, X., Skibniewski, M. J., Zhong, J., & Lu, Y. (2014). Bayesian-network-based safety risk analysis in construction projects. Reliability Engineering and System Safety, 131, 29–39. https://doi.org/10.1016/j.ress.2014.06.006
Zhang, L., Wu, X., Qin, Y., Skibniewski, M. J., & Liu, W. (2016). Towards a fuzzy Bayesian network based approach for safety risk analysis of tunnel-induced pipeline damage. Risk Analysis, 36(2), 278–301. https://doi.org/10.1111/risa.12448
Zhao, X., Hwang, B. G., & Gao, T. (2016). A fuzzy synthetic evaluation approach for risk assessment: a case of Singapore’s green projects. Journal of Cleaner Production, 115, 203–213. https://doi.org/10.1016/j.jclepro.2015.11.042
Abdollahzadeh, G., & Rastgoo, S. (2015). Risk assessment in bridge construction projects using fault tree and event tree analysis methods based on fuzzy logic. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 1(3), 031006. https://doi.org/10.1115/1.4030779
Andrić, J. M., & Lu, D. J. (2016). Risk assessment of bridges under multiple hazards in operation period. Safety Science, 83, 80–92. https://doi.org/10.1016/j.ssci.2015.11.001
Bobbio, A., Portinale, L., Minichino, M., & Ciancamerla, E. (2001). Improving the analysis of dependable systems by mapping fault trees into Bayesian networks. Reliability Engineering and System Safety, 71(3), 249–260. https://doi.org/10.1016/S0951-8320(00)00077-6
Bu-Qammaz, A. S., Dikmen, I., & Birgonul, M. T. (2009). Risk assessment of international construction projects using the analytic network process. Canadian Journal of Civil Engineering, 36(7), 1170–1181. https://doi.org/10.1139/L09-061
Cárdenas, I. C., Al-Jibouri, S. S., Halman, J. I., & van Tol, F. A. (2013). Modeling risk-related knowledge in tunneling projects. Risk Analysis, 34(2), 323–339. https://doi.org/10.1111/risa.12094
Chen, S. M., Munif, A., Chen, G. S., Liu, H. C., & Kuo, B. C. (2012). Fuzzy risk analysis based on ranking generalized fuzzy numbers with different left heights and right heights. Expert Systems with Applications, 39(7), 6320–6334. https://doi.org/10.1016/j.eswa.2011.12.004
Chen, T.-T., & Wang, C.-H. (2017). Fall risk assessment of bridge construction using Bayesian network transferring from fault tree analysis. Journal of Civil Engineering and Management, 23(2), 273–282. https://doi.org/10.3846/13923730.2015.1068841
Cheng, M., & Lu, Y. (2015). Developing a risk assessment method for complex pipe jacking construction projects. Automation in Construction, 58, 48–59. https://doi.org/10.1016/j.autcon.2015.07.011
Chien, K.-F., Wu, Z.-H., & Huang, S.-C. (2014). Identifying and assessing critical risk factors for BIM projects: Empirical study. Automation in Construction, 45, 1–15. https://doi.org/10.1016/j.autcon.2014.04.012
Deng, X., Pheng, L. S., & Zhao, X. (2014). Project system vulnerability to political risks in international construction projects: The case study of Chinese contractors. Project Management Journal, 45(2), 20–33. https://doi.org/10.1002/pmj.21397
El-Sayegh, S. M. (2008). Risk assessment and allocation in the UAE construction industry. International Journal of Project Management, 26(4), 431–438. https://doi.org/10.1016/j.ijproman.2007.07.004
Guo, C., Khan, F., & Imtiaz, S. (2019). Copula-based Bayesian network model for process system risk assessment. Process Safety and Environment Protection, 123, 317–326. https://doi.org/10.1016/j.psep.2019.01.022
Hu, Y., Zhang, X., Ngai, E. W. T., Cai, R., & Liu, M. (2013). Software project risk analysis using Bayesian networks with causality constraints. Decision Support Systems, 56, 439–449. https://doi.org/10.1016/j.dss.2012.11.001
Islam, M. S., Nepal, M. P., Skitmore, M., & Attarzadeh, M. (2017). Current research trends and application areas of fuzzy and hybrid methods to the risk assessment of construction projects. Advanced Engineering Informatics, 33, 112–131. https://doi.org/10.1016/j.aei.2017.06.001
John, A., Paraskevadakis, D., Bury, A., Yang, Z., Riahi, R., & Wang, J. (2014). An integrated fuzzy risk assessment for seaport operations. Safety Science, 68, 180–194. https://doi.org/10.1016/j.ssci.2014.04.001
John, A., Yang, Z., Riahi, R., & Wang, J. (2016). A risk assessment approach to improve the resilience of a seaport system using Bayesian networks. Ocean Engineering, 111, 136–147. https://doi.org/10.1016/j.oceaneng.2015.10.048
Kabir, G., Sadiq, R., & Tesfamariam, S. (2016). A fuzzy Bayesian belief network for safety assessment of oil and gas pipelines. Structure and Infrastructure Engineering, 12(8), 874–889. https://doi.org/10.1080/15732479.2015.1053093
Khakzad, N., Khan, F., & Amyotte, P. (2011). Safety analysis in process facilities: Comparison of fault tree and Bayesian network approaches. Reliability Engineering and System Safety, 96(8), 925–932. https://doi.org/10.1016/j.ress.2011.03.012
Khanzadi, M., Eshtehardian, E., & Mokhlespour Esfahani, M. (2017). Cash flow forecasting with risk consideration using Bayesian belief networks (BBNS). Journal of Civil Engineering and Management, 23(8), 1045–1059. https://doi.org/10.3846/13923730.2017.1374303
Khodakarami, V., & Abdi, A. (2014). Project cost risk analysis: A Bayesian networks approach for modeling dependences between cost items. International Journal of Project Management, 32(7), 1233–1245. https://doi.org/10.1016/j.ijproman.2014.01.001
Kuo, Y. C., & Lu, S. T. (2013). Using fuzzy multiple criteria decision making approach to enhance risk assessment for metropolitan construction projects. International Journal of Project Management, 31(4), 602–614. https://doi.org/10.1016/j.ijproman.2012.10.003
Leu, S. S., & Chang, C. M. (2013). Bayesian-network-based safety risk assessment for steel construction projects. Accidents Analysis and Prevention, 54, 122–133. https://doi.org/10.1016/j.aap.2013.02.019
Li, P., Chen, G., Dai, L., & Zhang, L. (2012). A fuzzy Bayesian network approach to improve the qualification of organizational influences in HRA frameworks. Safety Science, 50(7), 1569–1583. https://doi.org/10.1016/j.ssci.2012.03.017
Liu, J., Zhao, X., & Yan, P. (2016). Risk paths in international construction projects: case study from Chinese contractors. Journal of Construction Engineering and Management, 142(6), 05016002. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001116
Luu, V. T., Kim, S. Y., Tuan, N. V., & Qgunlana, S. O. (2009). Quantifying schedule risk in construction projects using Bayesian belief networks. International Journal of Project Management, 27(1), 39–50. https://doi.org/10.1016/j.ijproman.2008.03.003
Meng, X., Chen, G., Zhu, G., & Zhu, Y. (2019). Dynamic quantitative risk assessment of accidents induced by leakage on offshore platforms using DEMATEL-BN. International Journal of Naval Architecture and Ocean Engineering, 11(1), 22–32. https://doi.org/10.1016/j.ijnaoe.2017.12.001
Ojha, R., Ghadge, A., Tiwari, M. K., & Bititci, U. S. (2018). Bayesian network modelling for supply chain risk propagation. International Journal of Production Research, 56(17), 5795–5819. https://doi.org/10.1080/00207543.2018.1467059
Qazi, A., & Dikmen, I. (2019). From risk matrices to risk networks in construction projects. IEEE Transactions on Engineering Management (early access). https://doi.org/10.1109/TEM.2019.2907787
Qazi, A., Dickson, A., Quigley, J., & Gaudenzi, B. (2018). Supply chain risk network management: A Bayesian belief network and expected utility based approach for managing supply chain risks. International Journal of Production Economics, 196, 24–42. https://doi.org/10.1016/j.ijpe.2017.11.008
Rao, P. P. B., & Shankar, N. R. (2011). Ranking fuzzy numbers with a distance method using circumcenter of centroids and an index of modality. Advances in Fuzzy Systems, 178308. https://doi.org/10.1155/2011/178308
Ren, J., Jenkinson, I., Wang, J., Xu, D. L., & Yang, J. B. (2009). An offshore risk analysis method using fuzzy Bayesian network. Journal of Offshore Mechanics and Arctic Engineering, 131(4), 041101. https://doi.org/10.1115/1.3124123
Ross, T. J. (2004). Fuzzy logic with engineering applications (2nd ed.). Wiley.
Samantra, C., Datta, S., & Mahapatra, S. S. (2017). Fuzzy based risk assessment module for metropolitan construction project: An empirical study. Engineering Applications of Artificial Intelligence, 65, 449–464. https://doi.org/10.1016/j.engappai.2017.04.019
Seker, S., & Zavadskas, E. K. (2017). Application of fuzzy DEMATEL method for analyzing occupational risks on construction sites. Sustainability, 9(11), 2083. https://doi.org/10.3390/su9112083
Taylan, O., Bafail, A. O., Abdulaal, R. M. S., & Kabli, M. R. (2014). Construction projects selection and risk assessment by fuzzy AHP and fuzzy TOPSIS methodologies. Applied Soft Computing, 17, 105–116. https://doi.org/10.1016/j.asoc.2014.01.003
Valipour, A., Yahaya, N., Md Noor, N., Antuchevičienė, J., & Tamošaitienė, J. (2017). Hybrid SWARA-COPRAS method for risk assessment in deep foundation excavation project: An Iranian case study. Journal of Civil Engineering and Management, 23(4), 524–532. https://doi.org/10.3846/13923730.2017.1281842
Wang, T., Wang, S., Zhang, L., Huang, Z., & Li, Y. (2016). A major infrastructure risk-assessment framework: Application to a cross-sea route project in China. International Journal of Project Management, 34(7), 1403–1415. https://doi.org/10.1016/j.ijproman.2015.12.006
Wang, Z. Z., & Chen, C. (2017). Fuzzy comprehensive Bayesian network-based safety risk assessment for metro construction projects. Tunnelling and Underground Space Technology, 70, 330–342. https://doi.org/10.1016/j.tust.2017.09.012
Weber, P., Medina-Oliva, G., Simon, C., & Iung, B. (2012). Overview on Bayesian networks applications for dependability, risk analysis and maintenance areas. Engineering Applications of Artificial Intelligence, 25(4), 671–682. https://doi.org/10.1016/j.engappai.2010.06.002
Wilson, A. G., & Huzurbazar, A. V. (2007). Bayesian networks for multilevel system reliability. Reliability Engineering and System Safety, 92(10), 1413–1420. https://doi.org/10.1016/j.ress.2006.09.003
Wu, Y., Li, L., Xu, R., Chen, K., Hu, Y., & Lin, X. (2017). Risk assessment in straw-based power generation public-private partnership projects in China: A fuzzy synthetic evaluation analysis. Journal of Cleaner Production, 161, 977–990. https://doi.org/10.1016/j.jclepro.2017.06.008
Xu, Y., Yeung, J. F. Y., Chan, A. P. C., Chan, D. W. M., Wang, S. Q., & Ke, Y. (2010). Developing a risk assessment model for PPP projects in China–A fuzzy synthetic evaluation approach. Automation in Construction, 19(7), 929–943. https://doi.org/10.1016/j.autcon.2010.06.006
Yazdi, M., & Kabir, S. (2017). A fuzzy Bayesian network approach for risk analysis in process industries. Process Safety and Environmental Protection, 111, 507–519. https://doi.org/10.1016/j.psep.2017.08.015
Yildiz, A. E., Dikmen, I., Birgonul, M. T., Ercoskun, K., & Alten, S. (2014). A knowledge-based risk mapping tool for cost estimation of international construction projects. Automation in Construction, 43, 144–155. https://doi.org/10.1016/j.autcon.2014.03.010
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X
Zarei, E., Khakzad, N., Cozzani, V., & Reniers, G. (2019). Safety analysis of process systems using Fuzzy Bayesian Network (FBN). Journal of Loss Prevention in the Process Industries, 57, 7–16. https://doi.org/10.1016/j.jlp.2018.10.011
Zavadskas, E. K., Turskis, Z., & Tamosaitiene, J. (2010). Risk Assessment of Construction Projects. Journal of Civil Engineering and Management, 16(1), 33–46. https://doi.org/10.3846/jcem.2010.03
Zhang, L., Wu, X., Skibniewski, M. J., Zhong, J., & Lu, Y. (2014). Bayesian-network-based safety risk analysis in construction projects. Reliability Engineering and System Safety, 131, 29–39. https://doi.org/10.1016/j.ress.2014.06.006
Zhang, L., Wu, X., Qin, Y., Skibniewski, M. J., & Liu, W. (2016). Towards a fuzzy Bayesian network based approach for safety risk analysis of tunnel-induced pipeline damage. Risk Analysis, 36(2), 278–301. https://doi.org/10.1111/risa.12448
Zhao, X., Hwang, B. G., & Gao, T. (2016). A fuzzy synthetic evaluation approach for risk assessment: a case of Singapore’s green projects. Journal of Cleaner Production, 115, 203–213. https://doi.org/10.1016/j.jclepro.2015.11.042