This article explores the use of swarm intelligence algorithms in unmanned vehicles (UVs), focuses on their main advantages for improving the efficiency and productivity of systems. Unmanned vehicles, which can operate autonomously or under remote control, play a significant role in such areas as surveillance, search and rescue, agriculture and military operations.
This article presents the mathematical modeling of the multi-label classification task of job description texts aimed at the automatic detection of working conditions and social benefits, which can enhance communication efficiency between employers and job seekers. The proposed approach is based on the use of the transformer-based BERT neural network, pre-trained on a multilingual corpus. The dataset was constructed by collecting job postings from the three largest Ukrainian job search platforms: Work.ua, Robota.ua, and Jooble.org. The collected texts were augmented