| Popis: |
The shift from traditional agricultural mechanization to intelligent systems represents a cornerstone of modern agriculture, spurred by the IT revolution. This study investigates how cutting-edge measurement and control technologies can elevate the efficiency and intelligence of agricultural machinery. By employing advanced algorithms like particle filtering and SO-CDKF, alongside multi-feature fusion technology, we significantly enhance the precision and responsiveness of these systems. Our findings show a 15% improvement in measurement accuracy and a 20% reduction in response times for intelligent applications, with further efficiency gains from optimizing the fusion process. This research underscores the potential of intelligent technologies to transform agriculture, offering vital insights for its future development. |
