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Revolutionizing Pressure Sensors for Wild Migratory Bird Tracking

Scientists from the Aerospace Information Research Institute (AIR) at the Chinese Academy of Sciences (CAS) have introduced an enhanced algorithm known as Dynamic Quantum Particle Swarm Optimization (DQPSO) to enhance the precision and dependability of pressure sensors utilized in the tracking and monitoring of wild migratory birds.

Jessica rolletta shutterstockMegan craigChinese academy of sciencesAerospace information research instituteChinese academyDynamic quantum particle swarm optimizationIndustry focusRadial basis functionDynamic temperature compensationPressure sensorsMigratory bird biologging

New Algorithm Boosts Precision of Bird-Tracking Pressure Sensors

New Algorithm Boosts Precision of Bird-Tracking Pressure Sensors
miragenews.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from miragenews.com Daily Mail and Mail on Sunday newspapers.

Aerospace information research instituteChinese academy of sciencesElectronics on octChinese academyDynamic quantum particle swarm optimizationRadial basis function

Improved algorithm enhances precision of pressure sensors for wild bird tracking

Improved algorithm enhances precision of pressure sensors for wild bird tracking
phys.org - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from phys.org Daily Mail and Mail on Sunday newspapers.

Jinlu xieChinese academy of sciencesElectronics on octAerospace information research instituteChinese academyDynamic quantum particle swarm optimizationRadial basis functionDynamic temperature compensationPressure sensorsMigratory bird biologging applications