Quantifying Impacts of Construction Project Characteristics on Engineering Performance: A Fuzzy Neural Network Approach

Abstract

Performance of the different parties participating in a construction project, particularly engineering professionals, plays an important role in its successful or unsuccessful implementation. This paper presents a study conducted to investigate how project characteristics impact engineering performance in measurable terms. A comprehensive approach that benefits from the capabilities of fuzzy neural networks (FNNs), utility functions and the analytical hierarchy process (AHP) is specifically employed for such purpose. In this context, utility functions and AHP are integrated together to develop a n instrument for measuring engineering performance, while FNNs are used to develop a connectionist structure relating engineering performance to its influential project characteristics. For practicality, the study is implemented in the industrial construct ion sector. The paper begins with a discussion of the topic of engineering performance and the conventional methods for its measurement in the construction industry. Following is an overview of the adopted approach and the analytical capabilities it has. A fterwards, the paper presents the details of the system used for quantifying the sought impacts in the industrial construction sector, including, the basic architecture of the system and the data sets used in its development. Applying the developed system in quantifying the impact of example project characteristics is also illustrated. Lastly, conclusions of the study are drawn.