An adaptive neuro-fuzzy inference system (ANFIS)-based model was developed to predict the punching shear strength of flat concrete slabs without shear reinforcement. The model was developed using a database collected from 207 experiments available in the existing literature. Five key input parameters were used to build the model, which were slab effective depth, concrete strength, reinforcement ratio, yield tensile strength of reinforcement, and width of square loaded area. The output parameter of the model was punching shear strength. The results from the adaptive neural fuzzy inference model were compared to those from the simplified punching shear equations of ACI, BS-8110, Model Code 2010, Euro-Code 2, and also experimental results. The root mean square error (RMSE) and the correlation coefficient (R) were used as evaluation criteria. Parametric studies were presented using ANFIS to assess the effect of each input parameter on the punching shear strength and to compare ANFIS results to those from the equations proposed in commonly used codes. The results showed that the ANFIS model is simple and provided the most accurate predictions of the punching shear strength of two-way flat concrete slabs without shear reinforcement.

The “Failure Mode and Effects Analysis” (FMEA) is a widely recognized and practical method in reliability engineering. Its primary objective is to investigate, identify, and prioritize potential failure modes in a given system, design, operation, or service. However, it possesses several limitations. The present research employs a novel hybrid assessment model that combines the conventional FMEA with the “Adaptive Neuro-Fuzzy Inference System” (ANFIS) technique and “Fuzzy Analytic Hierarchy Process” (FAHP) method. The aim is to overcome the limitations of conventional FMEA and establish a system-based decision model that can serve as an efficient tool for evaluating and ranking potential trouble factors in construction projects, identifying suitable responses promptly and assisting the project management team in recovering troubled projects. The model proposed utilized the amalgamated impact (I _T) of cost and time, both of which are gauged via fuzzy AHP, alongside the Probability of Occurrence (P) and the degree of detection and control for potential trouble factors (DCD), as the basis for decision-making criteria, This (decision) is achieved by computing a trouble priority number. The hybrid approach was utilized to assess trouble factors in troubled construction projects. The findings demonstrate that the FMEA-ANFIS-FAHP model can provide a better assessment of trouble factors in construction projects experiencing difficulties. The hybrid model is a viable alternative to the conventional FMEA approach, as it mitigates various limitations and weaknesses inherent in the latter. Additionally, the hybrid model circumvents the need for many experts and expedites the assessment process.

Troubled construction projects are a global problem. Iraqi construction projects thus naturally suffer from this phenomenon, and, indeed, most Iraqi government Troubled construction projects are a global problem. Iraqi construction projects thus naturally suffer from this phenomenon, and, indeed, most Iraqi government