DFCluster: An efficient algorithm to mine maximal differential biclusters for single pilot operations task synthesis safety analysis

With the continuous advancement of the avionics system, crew members are correspondingly reduced, and Single Pilot Operations (SPO) has attracted widespread attention from scholars. To meet the flight requirements in SPO mode, it is necessary to further strengthen air-ground coordination system integration, but at the same time, there will be some safety issues caused by resource integration, function fusion, and task synthesis. Aimed at the safety problems caused by task synthesis, an efficient differential bicluster mining algorithm--DFCluster algorithm is proposed in this paper to discover potential hazardous elements or propagation mechanisms through mining the resource-function matrixes. To mine efficiently, several pruning techniques are designed for generating maximal biclusters without candidate maintenance. The experimental results show that the DFCluster algorithm is more efficient than the existing differential biclustering algorithms under different scales of artificial datasets and public datasets. Then, a typical flight scenario is designed based on SPO air-ground collaborative system architecture, and combined with our proposed DFCluster algorithm for task synthesis safety analysis. Based on the mining results, the SPO air-ground collaborative system architecture is modified, which ultimately improves the safety of the SPO system.