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Modelling the monthly abundance of Culicoides biting midges in nine European countries using Random Forests machine learning.

Parasites & vectors
BACKGROUND: Culicoides biting midges transmit viruses resulting in disease in ruminants and equids such as bluetongue, Schmallenberg disease and African horse sickness. In the past decades, these diseases have led to important economic losses for far...

Prioritizing and Analyzing the Role of Climate and Urban Parameters in the Confirmed Cases of COVID-19 Based on Artificial Intelligence Applications.

International journal of environmental research and public health
Nowadays, an infectious disease outbreak is considered one of the most destructive effects in the sustainable development process. The outbreak of new coronavirus (COVID-19) as an infectious disease showed that it has undesirable social, environmenta...

Forecasting beef production and quality using large-scale integrated data from Brazil.

Journal of animal science
With agriculture rapidly becoming a data-driven field, it is imperative to extract useful information from large data collections to optimize the production systems. We compared the efficacy of regression (linear regression or generalized linear regr...

Understanding climate phenomena with data-driven models.

Studies in history and philosophy of science
In climate science, climate models are one of the main tools for understanding phenomena. Here, we develop a framework to assess the fitness of a climate model for providing understanding. The framework is based on three dimensions: representational ...

Cherry Tomato Production in Intelligent Greenhouses-Sensors and AI for Control of Climate, Irrigation, Crop Yield, and Quality.

Sensors (Basel, Switzerland)
Greenhouses and indoor farming systems play an important role in providing fresh and nutritious food for the growing global population. Farms are becoming larger and greenhouse growers need to make complex decisions to maximize production and minimiz...

Improving area of occupancy estimates for parapatric species using distribution models and support vector machines.

Ecological applications : a publication of the Ecological Society of America
As geographic range estimates for the IUCN Red List guide conservation actions, accuracy and ecological realism are crucial. IUCN's extent of occurrence (EOO) is the general region including the species' range, while area of occupancy (AOO) is the su...

The Prediction of Hepatitis E through Ensemble Learning.

International journal of environmental research and public health
According to the World Health Organization, about 20 million people are infected with Hepatitis E every year. In 2015, there were 44,000 deaths due to HEV infection worldwide. Food, water and climate are key factors that affect the outbreak of Hepati...

The Influence of Climate Parameters on Maintenance of Wind Farms-A Galician Case Study.

Sensors (Basel, Switzerland)
There are different monitoring procedures in wind farms with two main objectives: (i) to improve energy production by the capability of the national electrical network and (ii) to reduce the stooped hours due to preventive and or corrective maintenan...

Coupling machine learning and crop modeling improves crop yield prediction in the US Corn Belt.

Scientific reports
This study investigates whether coupling crop modeling and machine learning (ML) improves corn yield predictions in the US Corn Belt. The main objectives are to explore whether a hybrid approach (crop modeling + ML) would result in better predictions...

Determining suitable machine learning classifier technique for prediction of malaria incidents attributed to climate of Odisha.

International journal of environmental health research
This study investigated the influence of climate factors on malaria incidence in the Sundargarh district, Odisha, India. The WEKA machine learning tool was used with two classifier techniques, Multi-Layer Perceptron (MLP) and J48, with three test opt...