A lot of hype has recently been generated around deep learning, a novel group of artificial
intelligence approaches able to break accuracy records in pattern recognition. Over the …

Temperature profoundly impacts both the phenotypes and distributions of organisms. These
thermal effects exert strong selective pressures on behaviour, physiology and life history …

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Supervised neural networks have been applied as a machine learning technique to identify
and predict emergent patterns among multiple variables. A common criticism of these …

Maps of species' distributions or habitat suitability are required for many aspects of
environmental research, resource management and conservation planning. These include …

With the growth of statistical modeling in the ecological sciences, researchers are using
more complex methods, such as artificial neural networks (ANNs), to address problems …

Artificial neural networks (ANNs) are receiving greater attention in the ecological sciences
as a powerful statistical modeling technique; however, they have also been labeled a “black …

In response to the exponentially increasing need to analyze vast amounts of data, Neural
Networks for Applied Sciences and Engineering: From Fundamentals to Complex Pattern …

Machine learning methods, a family of statistical techniques with origins in the field of
artificial intelligence, are recognized as holding great promise for the advancement of …

Recently flux tower data have become available for a variety of ecosystems under different
climatic and edaphic conditions. Although Flux tower data represent point measurements …