Research on Optimization of Tower Crane Position in High rise Buildings Based on Neural Networks

Abstract

In order to improve efficiency, the tower crane scheme for high-rise buildings should consider the reach distance of the crane, which directly affects the capacity of the crane and is directly related to the operating cost of the crane. This article proposes a neural network-based method for optimizing the position of high-rise building tower cranes to improve operational efficiency. The case study results indicate that this method can accurately estimate the capacity of the tower crane, automatically perform the result comparison process, improve the efficiency of the tower crane position optimization process, and reduce operating costs. This optimization model can be used to consider the operation plan of tower cranes or to design building layout planning when changing the trailer position during on-site construction.