Fei Song, Ran Wei, Chenzhou Wang, Yan Zhang
Residents' willingness towards first-contact with primary health care under uncertainty in healthcare: a cross-sectional study in rural China
BMJ open
main aim study utilize remote sensing data establish regression models machine learning predict locust density upcoming year first dataset monitoring grassland locust density constructed based meteorological data multisource remote sensing data study area subsequently svr support vector regression model bp neural network regression model random forest regression model bp neural network regression model pca principal component analysis deep belief network regression model built dataset experimental results show random forest regression model best prediction performance among five models specifically model achieved coefficient determination r2 09685 root mean square error rmse 10144 test set optimal values achieved among models tested finally locust density study area 2023 predicted comparing predicted results actual measured data found prediction accuracy high great significance local grassland ecological management disaster warning scientific decisionmaking support scientific research progress sustainable agricultural development