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Climate

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Delineation of high resolution climate regions over the Korean Peninsula using machine learning approaches.

PloS one
In this research, climate classification maps over the Korean Peninsula at 1 km resolution were generated using the satellite-based climatic variables of monthly temperature and precipitation based on machine learning approaches. Random forest (RF), ...

Comparison of neuron-based, kernel-based, tree-based and curve-based machine learning models for predicting daily reference evapotranspiration.

PloS one
Accurately predicting reference evapotranspiration (ET0) with limited climatic data is crucial for irrigation scheduling design and agricultural water management. This study evaluated eight machine learning models in four categories, i.e. neuron-base...

Urban population exposure to tropospheric ozone: A multi-country forecasting of SOMO35 using artificial neural networks.

Environmental pollution (Barking, Essex : 1987)
Urban population exposure to tropospheric ozone is a serious health concern in Europe countries. Although there are insufficient evidence to derive a level below which ozone has no effect on mortality WHO (World Health Organization) uses SOMO35 (sum ...

Machine learning modeling of plant phenology based on coupling satellite and gridded meteorological dataset.

International journal of biometeorology
Changes in the timing of plant phenological phases are important proxies in contemporary climate research. However, most of the commonly used traditional phenological observations do not give any coherent spatial information. While consistent spatial...

The utility of LASSO-based models for real time forecasts of endemic infectious diseases: A cross country comparison.

Journal of biomedical informatics
INTRODUCTION: Accurate and timely prediction for endemic infectious diseases is vital for public health agencies to plan and carry out any control methods at an early stage of disease outbreaks. Climatic variables has been identified as important pre...

Eyes on our planet.

Current biology : CB
Combining several satellite-based tracking technologies with big data methods and machine learning, fisheries experts can now efficiently monitor the entirety of the oceans and ensure that legal limits and protected areas are respected. Observing our...

A bioavailable strontium isoscape for Western Europe: A machine learning approach.

PloS one
Strontium isotope ratios (87Sr/86Sr) are gaining considerable interest as a geolocation tool and are now widely applied in archaeology, ecology, and forensic research. However, their application for provenance requires the development of baseline mod...

Developing a dengue forecast model using machine learning: A case study in China.

PLoS neglected tropical diseases
BACKGROUND: In China, dengue remains an important public health issue with expanded areas and increased incidence recently. Accurate and timely forecasts of dengue incidence in China are still lacking. We aimed to use the state-of-the-art machine lea...

[Applications of eco-environmental big data: Progress and prospect].

Ying yong sheng tai xue bao = The journal of applied ecology
With the advance of internet and wireless communication technology, the fields of ecology and environment have entered a new digital era with the amount of data growing explosively and big data technologies attracting more and more attention. The eco...