Publications / 2020 Proceedings of the 37th ISARC, Kitakyushu, Japan

Applying ANN to the AI Utilization in Forecasting Planning Risks in Construction

Fawaz Habbal, Firas Habbal, Abdualla Alnuaimi, Anwar Alshimmari, Nawal Alhanaee and Ammar Safi
Pages 1431-1437 (2020 Proceedings of the 37th ISARC, Kitakyushu, Japan, ISBN 978-952-94-3634-7, ISSN 2413-5844)
Abstract:

A long-standing problem in the field of automated reasoning is designing systems that can describe a set of actions (or a plan) that can be expected to allow the system to reach the desired goal. Artificial Intelligence (AI) techniques provide the means to generate plans and to reason with as well as provide explanations from stored knowledge. However, these methods, which employ little domain knowledge and are originally used in AI for planning, proved inadequate for complex real-life problems such as project planning. As a result, more recent research adopts the knowledge engineering methodology as an efficient approach for developing planning systems. This paper highlights the limitations of existing project planning tools. It also illustrates the power of AI techniques in the construction planning domain through a summary and critique of previous and current research in AI planning. It then concludes with a suggested approach for development. From the study, it was found out that a proper application of the AI technology requires full support in form of a Data Bank, which, unfortunately, becomes one of the most significant hurdles in its adoption. To deal with this limitation, it is recommended to adopt the ANN.

Keywords: Risks Planning; Construction Planning; Risks forecasting; Neural Network; Support Vector Machines