Abstract: Aiming at the problem that it is difficult to accurately predict the air-conditioning system’s energy consumption in underground engineering， an energy consumption prediction model based on the eXtreme Gradient Boosting algorithm （XGBoost） optimized by the Beetle Antennae Search （BAS） algorithm is proposed. The algorithm optimizes the position update strategy in the conventional beetle algorithm by introducing a typical optimal solution guidance mechanism， and uses a linear decreasing strategy to correct the search step size of the beetle， so as to achieve the global optimum point and improve the convergence speed. The number of decision trees and the maximum depth of the tree in XGBoost， which have a greater impact on the prediction accuracy of the mode， are used to optimize by the improved BAS， so as to obtain the optimal parameter combination of XGBoost and improve the model prediction accuracy. Finally， taking the air-conditioning system of an underground security project as the research object， the validity of the proposed prediction model is verified.

Key words: underground engineering, load forecast, eXtreme gradient boosting, improved beetle antennae search algorithm