Application of neural networks and neuro-fuzzy models in construction scheduling.

ABSTRACT: Construction scheduling is a complex process that involves a large number of variables, making it difficult to develop accurate and efficient schedules. Traditional scheduling techniques rely on manual analysis and intuition, which are prone to errors and often fail to account for all the variables involved. This results in project delays, cost overruns, and poor project performance. Artificial intelligence models have shown promise in improving construction scheduling accuracy by incorporating historical data, site-specific conditions, and other variables that traditional scheduling methods may not consider. In this research study, application of soft-computing techniques to evaluate construction schedule and control of project activities in order to achieve optimal performance in executi

SUBMITTER: Obianyo JI 

PROVIDER: S-EPMC10200797 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature