AIMC Topic: Seasons

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Comparison of autoregressive integrated moving average model and generalised regression neural network model for prediction of haemorrhagic fever with renal syndrome in China: a time-series study.

BMJ open Jun 16, 2019
OBJECTIVES: Haemorrhagic fever with renal syndrome (HFRS) is a serious threat to public health in China, accounting for almost 90% cases reported globally. Infectious disease prediction may help in disease prevention despite some uncontrollable influ...
Humans Neural Networks, Computer Incidence Models, Statistical Software Seasons Hemorrhagic Fever with Renal Syndrome Forecasting China
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Development and evaluation of a deep learning approach for modeling seasonality and trends in hand-foot-mouth disease incidence in mainland China.

Scientific reports May 29, 2019
The high incidence, seasonal pattern and frequent outbreaks of hand, foot, and mouth disease (HFMD) represent a threat for millions of children in mainland China. And advanced response is being used to address this. Here, we aimed to model time serie...
Humans Forecasting Computer Simulation Epidemics Epidemiological Monitoring Hand, Foot and Mouth Disease Child, Preschool Models, Statistical Seasons Datasets as Topic Deep Learning China Incidence
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Time series analysis of human brucellosis in mainland China by using Elman and Jordan recurrent neural networks.

BMC infectious diseases May 14, 2019
BACKGROUND: Establishing epidemiological models and conducting predictions seems to be useful for the prevention and control of human brucellosis. Autoregressive integrated moving average (ARIMA) models can capture the long-term trends and the period...
Recurrence Jordan Brucellosis Models, Statistical Humans Seasons Neural Networks, Computer China Incidence
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Deep learning and process understanding for data-driven Earth system science.

Nature Feb 13, 2019
Machine learning approaches are increasingly used to extract patterns and insights from the ever-increasing stream of geospatial data, but current approaches may not be optimal when system behaviour is dominated by spatial or temporal context. Here, ...
Pattern Recognition, Automated Geographic Mapping Knowledge Translating Time Factors Weather Seasons Regression, Psychology Uncertainty Facial Recognition Earth Sciences Forecasting Computer Simulation Female Reproducibility of Results Spatio-Temporal Analysis Humans Deep Learning Big Data
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Seasonal Variation in Essential Oils Composition and the Biological and Pharmaceutical Protective Effects of Leaves Grown in Tunisia.

BioMed research international Dec 9, 2018
This research assessed the seasonal variation of the chemical composition and antibacterial and anticholinesterase activities of essential oils extracted from leaves. The leaves organic fractions were also investigated for their biological activitie...
Mentha Animals Tunisia Oils, Volatile Humans Bacteria Rats, Wistar Flavonoids Anti-Bacterial Agents Rats Seasons Neuroprotective Agents Alzheimer Disease Plant Leaves
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Do reductions in agricultural field drainage during the growing season impact bacterial densities and loads in small tile-fed watersheds?

Water research Nov 30, 2018
Predicting bacterial levels in watersheds in response to agricultural beneficial management practices (BMPs) requires understanding the germane processes at both the watershed and field scale. Controlling subsurface tile drainage (CTD) is a highly ef...
Seasons Rivers Bacteria Agriculture Escherichia coli
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Defining heatwave thresholds using an inductive machine learning approach.

PloS one Nov 7, 2018
Establishing appropriate heatwave thresholds is important in reducing adverse human health consequences as it enables a more effective heatwave warning system and response plan. This paper defined such thresholds by focusing on the non-linear relatio...
Meteorology Humans Supervised Machine Learning Extreme Heat Hospitalization Seasons Male Aged Heat Stress Disorders Middle Aged Young Adult Adolescent Adult Emergency Service, Hospital
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Priorization of River Restoration by Coupling Soil and Water Assessment Tool (SWAT) and Support Vector Machine (SVM) Models in the Taizi River Basin, Northern China.

International journal of environmental research and public health Sep 23, 2018
Identifying priority zones for river restoration is important for biodiversity conservation and catchment management. However, limited data due to the difficulty of field collection has led to research to better understand the ecological status withi...
Seasons Rivers Soil Hydrology Animals Environmental Restoration and Remediation China Aquatic Organisms Environmental Monitoring Biodiversity Support Vector Machine
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Forecasting air quality time series using deep learning.

Journal of the Air & Waste Management Association (1995) May 24, 2018
UNLABELLED: This paper presents one of the first applications of deep learning (DL) techniques to predict air pollution time series. Air quality management relies extensively on time series data captured at air monitoring stations as the basis of ide...
Particulate Matter Seasons Environmental Monitoring Air Pollutants Air Pollution Ozone Forecasting Deep Learning
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Dengue forecasting in São Paulo city with generalized additive models, artificial neural networks and seasonal autoregressive integrated moving average models.

PloS one Apr 2, 2018
Globally, the number of dengue cases has been on the increase since 1990 and this trend has also been found in Brazil and its most populated city-São Paulo. Surveillance systems based on predictions allow for timely decision making processes, and in ...
Algorithms Forecasting Reproducibility of Results Brazil Dengue Models, Statistical Population Surveillance Humans Seasons Neural Networks, Computer
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