An Evolutionary Algorithm-based Method for Estimating the Expected Construction Volume of Building Works

The current conventional estimation method of expected construction volume of building works mainly achieves the estimation of construction volume by matching between the quantity table and estimation rules, which leads to poor estimation due to the low dimensionality of selected estimation indexes. In this regard, the method of estimating construction volume based on evolutionary algorithm is proposed. The construction volume estimation indexes are extracted by analyzing the main factors affecting the construction volume of construction projects. And the main structure of the construction volume estimation model is constructed by combining the neural network algorithm, the parameters of each layer and the number of output nodes are set, and finally the designed construction volume estimation model is combined with the evolutionary algorithm for seven sessions. In the experiments, the designed construction volume estimation model is verified for the estimation accuracy. The final results can prove that the estimation error value is low and has high estimation accuracy when the proposed method is used to estimate the construction volume.