Naslov
Deep and reinforcement learning in mosquito population control

Autori
Hackenberger Kutuzović, Domagoj ; Đerđ, Tamara ; Hackenberger Kutuzović, Branimir

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

Izvornik
6th Faculty of Science PhD Student Symposium - Book of Abstracts / Đaković, Marijana ; Korać, Petra ; Lukić, Aleksandar ; Marušić-Paloka, Eduard ; Novak, Predrag ; Pezelj, Đurđica ; Pikelj, Kristina ; Smolčić, Vernesa ; Schneider, Petra - Zagreb, 2022, 198-199

ISBN
978-953-6076-93-2

Skup
6. Simpozij studenata doktorskih studija PMF-a = 6th Faculty of Science PhD Student Symposium

Mjesto i datum
Zagreb, Hrvatska, 23.04.2022. - 24.04.2022

Vrsta sudjelovanja
Poster

Vrsta recenzije
Domaća recenzija

Ključne riječi
computer simulations ; optimization

Sažetak
Because of climate change, an increase in the risk of vector-borne diseases has been reported. Mosquitoes are dominant vectors of most of these diseases. Therefore, the rapid monitoring of mosquito population dynamics it is of the utmost importance. In this work, the framework of a multi-layered decision support system for the control of the mosquito population is described. Layers of the framework combine biological knowledge, Internet of Things (IoT), big data, and state- of-the-art AI techniques, such as deep and reinforcement learning, and population modeling, to make a decision support system that will be able to automatically survey mosquito population dynamics and devise a strategy for population control.

Izvorni jezik
Engleski

Znanstvena područja
Biologija, Interdisciplinarne prirodne znanosti

POVEZANOST RADA