The study of artificial intelligence for predicting land use changes in an arid ecosystem

During the 21st century, artificial intelligence methods have been broadly applied in geosciences to simulate complex dynamic ecosystems, but use of (AI) reproduce land-use/cover change (LUCC) arid ecosystems remains rare. This paper presents a hybrid modeling approach understand complexity LUCC. Fuzzy logic, equation-based systems, and expert systems are combined predict LUCC as determined by water resources other factors. The driving factors this study include climate change, ecological flooding, groundwater conditions, human activities. increase natural flooding was found be effective preventing vegetation degradation. LUCCs sensitive under different projections RCP2.6, RCP4.5, RCP8.5. Simulation results indicate that precipitation is not able compensate for additional evaporation losses resulting from temperature increases. grassland, shrub, riparian forest regions will shrink area. grasslands has strong negative correlation with salinity, whereas had positive flooding. application can guide land management policies make predictions regarding