Zhao, Y; Chen, W; Arashpour, M; Yang, Z; Shao, C and Li, C (2022) Predicting delays in prefabricated projects: Sd-bp neural network to define effects of risk disruption. Engineering, Construction and Architectural Management, 29(4), pp. 1753-1776. ISSN 0969-9988
Abstract
Purpose: Prefabricated construction is often hindered by scheduling delays. This paper aims to propose a schedule delay prediction model system, which can provide the key information for controlling the delay effects of risk-related factors on scheduling in prefabricated construction. Design/methodology/approach: This paper combines SD (System Dynamics) and BP (Back Propagation) neural network to predict risk related delays. The SD-based prediction model focuses on dynamically presenting the interrelated impacts of risk events and activities along with workflow. While BP neural network model is proposed to evaluate the delay effect for a single risk event disrupting a single job, which is the necessary input parameter of SD-based model. Findings: The established model system is validated through a structural test, an extreme condition test, a sensitivity test, and an error test, and shows an excellent performance on aspect of reliability and accuracy. Furthermore, 5 scenarios of case application during 3 different projects located in separate cities prove the prediction model system can be applied in a wide range. Originality/value: This paper contributes to academic research on combination of SD and BP neural network at the operational level prediction, and a practical prediction tool supporting managers to take decision-making in a timely manner against delays.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | bp neural network; predicting delays; prefabricated construction; risk disruption; system dynamics |
| Index terms: | back propagation, schedule delay, bp neural network, prediction model, accuracy, neural network, scheduling, manager, workflow, system dynamics, decision-making, methodology |
| Subjects: | project controls, decision analysis, management, research methods, algorithms, professional development, operations research, artificial intelligence, prediction and forecasting, computing systems, practitioner |
| Topics: | Digital Applications, Time Control, Business Strategy, Research Practice, Information Management, Roles and Professions, Risk Management |
| Descriptive scope: | 4 PCTA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here