Methodology for integrating fuzzy expert systems and discrete event simulation in construction engineering

2009 ◽  
Vol 36 (9) ◽  
pp. 1478-1490 ◽  
Author(s):  
Ahmed A. Shaheen ◽  
Aminah Robinson Fayek ◽  
Simaan M. AbouRizk

This paper demonstrates how fuzzy expert systems can be integrated within discrete event simulation models to enhance their modeling and predictive capabilities for construction engineering applications. A proposed methodology is presented for extracting the information from experts to develop the fuzzy expert system rules. The developed fuzzy expert system is integrated within a discrete event simulation model to enhance its modeling capability by explicitly accounting for the different factors affecting some of the simulation activities. A tunneling case study is used to illustrate the features of the integrated system. The outputs generated from the integrated system are very comparable to those from the original probabilistic simulation model. The integrated system represents a more realistic modeling scenario, since it thoroughly accounts for the different factors affecting the tunnel boring machine (TBM) advance rate. This paper is relevant to researchers because it provides an advance in combining artificial intelligence techniques with simulation models to yield better tools for construction modeling. It is of relevance to practitioners because it provides a useful tool for modeling construction engineering problems.

2012 ◽  
Vol 32 (3) ◽  
pp. 543-560 ◽  
Author(s):  
Alexandre Ferreira de Pinho ◽  
José Arnaldo Barra Montevechi ◽  
Fernando Augusto Silva Marins ◽  
Rafael Florêncio da Silva Costa ◽  
Rafael de Carvalho Miranda ◽  
...  

Author(s):  
Ming Dong ◽  
Jianzhong Cha ◽  
Mingcheng E

Abstract In this paper, we realize knowledge-based discrete event simulation model’s representation, reasoning and implementation by means of object-oriented(OO) frame language. Firstly, a classes library of simulation models is built by using the OO frame language. And then, behaviours of simulation models can be generated by inference engines reasoning about knowledge base. Lastly, activity cycle diagrams can be used to construct simulation network logic models by connecting the components classes of simulation models. This kind of knowledge-based simulation models can effectively solve the modeling problems of complex and ill-structure systems.


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