Predicting construction costs often involves disadvantages, such as low prediction accuracy, poor promotion value and unfavorable efficiency, owing to the complex composition of construction projects, a large number of personnel, long working periods and high levels of uncertainty. To address these concerns, a prediction index system and a prediction model were developed. First, the factors influencing construction cost were first identified, a prediction index system including 14 secondary indexes was constructed and the methods of obtaining data were presented elaborately. A prediction model based on the Random Forest (RF) algorithm was then constructed. Bird Swarm Algorithm (BSA) was used to optimize RF parameters and thereby avoid the effect of the random selection of RF parameters on prediction accuracy. Finally, the engineering data of a construction company in Xinyu, China were selected as a case study. The case study showed that the maximum relative error of the proposed model was only 1.24%, which met the requirements of engineering practice. For the selected cases, the minimum prediction index system that met the requirement of prediction accuracy included 11 secondary indexes. Compared with classical metaheuristic optimization algorithms (Particle Swarm Optimization, Genetic Algorithms, Tabu Search, Simulated Annealing, Ant Colony Optimization, Differential Evolution and Artificial Fish School), BSA could more quickly determine the optimal combination of calculation parameters, on average. Compared with the classical and latest forecasting methods (Back Propagation Neural Network, Support Vector Machines, Stacked Auto-Encoders and Extreme Learning Machine), the proposed model exhibited higher forecasting accuracy and efficiency. The prediction model proposed in this study could better support the prediction of construction cost, and the prediction results provided a basis for optimizing the cost management of construction projects.

Scholars and engineers have increasingly focused on the safety of steel-structure buildings. An accurate analysis can substantially reduce the collapse probability of these buildings. This paper proposes a novel risk analysis model to assess the safety of steel-structure buildings. The vector entropy method and weight clustering were used to improve the controlled interval and memory (CIM) model. The proposed model has the advantages of a straightforward modeling approach, strong adaptability, and logical relationships. The new strategy improves the reliability and stability of the CIM model results when the maximum membership principle is not applicable. The Jiangxi Exhibition Center in China, which has a steel truss roof, is used as a case study. The results indicate a high safety risk of the project and the need for maintenance and repair. The improved CIM model has higher stability and adaptability for analyzing the safety risks of steel structure than the standard CIM model.

To study the mechanical properties of asymmetric K-shaped square tubular joints with built-in stiffening rib lap joints, axial tensile tests were carried out on one K-shaped joint without built-in stiffening ribs and four K-shaped joints with built-in stiffening ribs using an electro-hydraulic servo structural testing system. The effects of the addition of stiffening ribs and the welding method of the stiffening ribs on the mechanical properties were studied comparatively. The failure mode of the K-shaped joint was obtained, and the strain distribution and peak displacement reaction force in the nodal region were analyzed. A finite element analysis of the K-shaped joint was carried out, and the finite element results were compared with the experimental results. The results showed that the addition of transverse reinforcement ribs and more complete welds shared the squeezing effect of the brace on the chord. Arranging more reinforcing ribs in the fittings makes the chord more uniformly stressed and absorbs more energy while increasing the flexural load capacity of the fittings’ side plates. The presence of a weld gives a short-lived temperature increase in the area around the crack, and the buckling of the structure causes the surface temperature in the buckling area to continue to increase for some time. The temperature change successfully localized where the structure was deforming and creating cracks. The addition of the reinforcing ribs resulted in a change in the deformation pattern of the model, and the difference occurred because the flexural capacity of the brace with the added reinforcing ribs was greater than that of the side plate buckling.