Efficient spatial prediction models for soil heavy metals are crucial for maintaining soil ecosystem health, promoting high-quality regional agriculture, and national food security. Traditional machine learning (ML) models often overlook spatial auto...
Probabilistic Random Forest is an extension of the traditional Random Forest machine learning algorithm that is one of the frequently used machine learning algorithms employed for species distribution modeling. However, with the use of complex datase...
BACKGROUND: Educational hypogamy, where women marry men with lower educational attainment, reflects evolving gender roles and societal norms. In China, the rapid expansion of education, coupled with persistent traditional values, provides a unique co...
Asthma is a frequent and long-lasting disorder associated with airway inflammation. The disease severity may lead to serious health concerns and even mortality. In this work, we propose a novel hybrid approach using machine learning models and simila...
Schizophrenia is a complex neuropsychiatric disorder with cognitive deficits and systemic physiological disturbances, including emerging links to hepatic dysfunction via the gut-liver-brain axis. Despite growing evidence, the integration of liver fun...
Cultivated land is one of the most valuable agricultural resources; its quality is not only the foundation of national food security but also a crucial issue for global sustainable development. However, owing to data limitations and spatial heterogen...
Rapid and disorderly urban expansion leads to productivity loss, habitat fragmentation, and reduced land marginal returns, hindering sustainable urban development. Scientific identification of land use conflicts (LUCs) and understanding their driving...
The rapid expansion of online education has intensified the need to investigate the multifactorial determinants of university students' satisfaction with digital learning platforms. While prior studies have often examined technical or pedagogical com...
Birds have adapted to climatic and ecological cycles to inform their Spring and Fall migration timings, but anthropogenic global warming has affected these long-establish cycles. Understanding these dynamics is critical for conservation during a chan...
Random Forest (RF) is a powerful ensemble-based supervised machine learning technique that builds multiple decision trees using bootstrap aggregating and random feature selection to improve classification and regression accuracy while reducing overfi...
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