The Engineering Cost Evaluation Based on IPSO

The rough set theory was used to reduce the factors affecting construction engineering cost and optimize input variables of BP neural network. Then, the improved particle swarm algorithm with constriction factors is adopted to optimize the initial weights and thresholds. An engineering project in a city of Hunan is selected to make empirical analysis. It shows that based on the features of engineering, this new model enjoys a high practical value as it can be applied to make scientific evaluation of costs of construction engineering.