TY - GEN
T1 - Accommodating Uncertainty in Forecast Generation of Artificial Intelligence Tools in Construction Projects
AU - Zarghami, Seyed Ashkan
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Plagued by considerable uncertainty, construction management requires an outside view to increase the reliability of reference class forecasting (RCF). Accordingly, artificial intelligence (AI) tools are used in this approach to reduce such uncertainty in RCF. More explicitly, the outside view adopts the performance of past similar projects to predict that of the future project. As widely acknowledged in the literature, the similarity between the selected reference and the new project is of paramount importance. Despite this, the previous literature did not show how to measure the extent of the similarity to the new project. This study was conducted to fill this important gap by proposing a measure of similarity. The proposed measure can be used to quantify how previous projects were distributed. In the proposed method, eight real-life construction projects were analyzed using AI tools to select a highly comparable reference to the project.
AB - Plagued by considerable uncertainty, construction management requires an outside view to increase the reliability of reference class forecasting (RCF). Accordingly, artificial intelligence (AI) tools are used in this approach to reduce such uncertainty in RCF. More explicitly, the outside view adopts the performance of past similar projects to predict that of the future project. As widely acknowledged in the literature, the similarity between the selected reference and the new project is of paramount importance. Despite this, the previous literature did not show how to measure the extent of the similarity to the new project. This study was conducted to fill this important gap by proposing a measure of similarity. The proposed measure can be used to quantify how previous projects were distributed. In the proposed method, eight real-life construction projects were analyzed using AI tools to select a highly comparable reference to the project.
KW - artificial intelligence (AI) tools
KW - construction projects
KW - outside view
KW - reference class forecasting
UR - http://www.scopus.com/inward/record.url?scp=85187237823&partnerID=8YFLogxK
U2 - 10.1109/ICACEH59552.2023.10452587
DO - 10.1109/ICACEH59552.2023.10452587
M3 - Conference contribution
AN - SCOPUS:85187237823
T3 - 2023 IEEE 5th International Conference on Architecture, Construction, Environment and Hydraulics, ICACEH 2023
SP - 8
EP - 11
BT - 2023 IEEE 5th International Conference on Architecture, Construction, Environment and Hydraulics, ICACEH 2023
A2 - Meen, Teen-Hang
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th IEEE International Conference on Architecture, Construction, Environment and Hydraulics, ICACEH 2023
Y2 - 1 December 2023 through 3 December 2023
ER -