Smart Management of Sand-Breaking Systems for Taklimakan SandSea Highway: A Parallel Intelligence and Fuzzy Control Approach

The planning, construction, and maintenance of sand-breaking systems around highway in Taklimakan SandSea mainly depend on expert's empirical knowledge, and face the problems of time-consuming management, unpredictable system performance, and few available data. This work proposes a management and control method of sand-breaking systems that follows artificial system, computational experiments, and parallel execution (ACP) theory. Expert knowledge was extracted to develop artificial sand-breaking system. conditional tabular generative adversarial network (CTGAN) was developed to achieve data augmentation. Computational experiments were implemented to evaluate artificial system performance by predicting whether the system can reach the set age limit. Using fuzzy control, the real sand-breaking system and the artificial one can learn from each other in parallel execution to provide decision support for sand-breaking system management. This approach provides a human–machine hybrid parallel intelligence system for complex sand-breaking systems management.