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Applications of machine learning (ML) in earth sciences include geological mapping, gas leakage detection and geological feature identification.Machine learning is a subdiscipline of artificial intelligence aimed at developing programs that are able to classify, cluster, identify, and analyze vast and complex data sets without the need for explicit programming to do so. [1]
Machine learning may also provide predictions to farmers at the point of need, such as the contents of plant-available nitrogen in soil, to guide fertilization planning. [59] As more agriculture becomes ever more digital, machine learning will underpin efficient and precise farming with less manual labour.
DIVA-GIS has an easy to use (and good for educational use) implementation of BIOCLIM The Biodiversity and Climate Change Virtual Laboratory (BCCVL) is a "one stop modelling shop" that simplifies the process of biodiversity and climate impact modelling. It connects the research community to Australia's national computational infrastructure by ...
Machine learning in environmental metagenomics can help to answer questions related to the interactions between microbial communities and ecosystems, e.g. the work of Xun et al., in 2021 [50] where the use of different machine learning methods offered insights on the relationship among the soil, microbiome biodiversity, and ecosystem stability.
There are dozens of erosion prediction models.Some models focus on long-term (natural or geological) erosion, as a component of landscape evolution.However, many erosion models were developed to quantify the effects of accelerated soil erosion i.e. soil erosion as influenced by human activity.
There is one novel machine learning framework for fire prediction, which represents a significant contribution to computational sustainability in the field of environmental monitoring. The model, centered on the identification of specific ignitions likely to lead to large fires, provides a more straightforward and interpretable alternative to ...
Your brain health matters! BrainHQ rewires the brain so you can think faster, focus better, and remember more. And that helps people feel happier, healthier, and more in control.
The first clinical prediction model reporting guidelines were published in 2015 (Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD)), and have since been updated. [10] Predictive modelling has been used to estimate surgery duration.