AIMC Topic: Weather

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Transductive LSTM for time-series prediction: An application to weather forecasting.

Neural networks : the official journal of the International Neural Network Society Jan 8, 2020
Long Short-Term Memory (LSTM) has shown significant performance on many real-world applications due to its ability to capture long-term dependencies. In this paper, we utilize LSTM to obtain a data-driven forecasting model for an application of weath...
Neural Networks, Computer Weather
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Toward safer highways, application of XGBoost and SHAP for real-time accident detection and feature analysis.

Accident; analysis and prevention Dec 20, 2019
Detecting traffic accidents as rapidly as possible is essential for traffic safety. In this study, we use eXtreme Gradient Boosting (XGBoost)-a Machine Learning (ML) technique-to detect the occurrence of accidents using a set of real time data compri...
Humans Built Environment Chicago Machine Learning Models, Statistical Accidents, Traffic Weather Spatial Analysis
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Deep learning for pollen allergy surveillance from twitter in Australia.

BMC medical informatics and decision making Nov 8, 2019
BACKGROUND: The paper introduces a deep learning-based approach for real-time detection and insights generation about one of the most prevalent chronic conditions in Australia - Pollen allergy. The popular social media platform is used for data colle...
Rhinitis, Allergic, Seasonal Australia Social Media Algorithms Weather Deep Learning Humans
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Applying machine learning to forecast daily Ambrosia pollen using environmental and NEXRAD parameters.

Environmental monitoring and assessment Jun 28, 2019
Approximately 50 million Americans have allergic diseases. Airborne plant pollen is a significant trigger for several of these allergic diseases. Ambrosia (ragweed) is known for its abundant production of pollen and its potent allergic effect in Nort...
Weather Antigens, Plant Hypersensitivity Radar Forecasting Plant Extracts Environmental Monitoring Humans Machine Learning
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Estimating the daily pollen concentration in the atmosphere using machine learning and NEXRAD weather radar data.

Environmental monitoring and assessment Jun 7, 2019
Millions of people have an allergic reaction to pollen. The impact of pollen allergies is on the rise due to increased pollen levels caused by global warming and the spread of highly invasive weeds. The production, release, and dispersal of pollen de...
Antigens, Plant Atmosphere Radar Pollen Environmental Monitoring Weather Allergens Oklahoma Forecasting Plant Extracts Machine Learning
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Applying Deep Neural Networks and Ensemble Machine Learning Methods to Forecast Airborne Pollen.

International journal of environmental research and public health Jun 4, 2019
Allergies to airborne pollen are a significant issue affecting millions of Americans. Consequently, accurately predicting the daily concentration of airborne pollen is of significant public benefit in providing timely alerts. This study presents a me...
Weather Allergens Antigens, Plant Ambrosia Forecasting Neural Networks, Computer Plant Extracts Machine Learning Bayes Theorem
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Real-time accident detection: Coping with imbalanced data.

Accident; analysis and prevention Jun 3, 2019
Detecting accidents is of great importance since they often impose significant delay and inconvenience to road users. This study compares the performance of two popular machine learning models, Support Vector Machine (SVM) and Probabilistic Neural Ne...
Time Factors Support Vector Machine Accidents, Traffic Weather Humans Neural Networks, Computer Chicago
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Unveiling tropospheric ozone by the traditional atmospheric model and machine learning, and their comparison:A case study in hangzhou, China.

Environmental pollution (Barking, Essex : 1987) May 27, 2019
Tropospheric ozone in the surface air has become the primary atmospheric pollutant in Hangzhou, China, in recent years. Previous analysis is not enough to decode it for better regulation. Therefore, we use the traditional atmospheric model, Weather R...
Environmental Monitoring Air Pollutants Meteorological Concepts Air Pollution Volatile Organic Compounds Machine Learning Meteorology Forecasting Ozone Neural Networks, Computer Wind Weather China
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Research on soil moisture prediction model based on deep learning.

PloS one Apr 3, 2019
Soil moisture is one of the main factors in agricultural production and hydrological cycles, and its precise prediction is important for the rational use and management of water resources. However, soil moisture involves complex structural characteri...
Droughts Meteorology Water Agriculture Models, Theoretical Weather Groundwater Agricultural Irrigation Algorithms Regression Analysis Temperature Soil Reproducibility of Results Deep Learning China
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Deep learning for identifying environmental risk factors of acute respiratory diseases in Beijing, China: implications for population with different age and gender.

International journal of environmental health research Mar 31, 2019
This study focuses on identifying environmental health risk factors related to acute respiratory diseases using deep learning method. Based on respiratory disease data, air pollution data and meteorological environmental data, cross-domain risk facto...
Age Factors Acute Disease Air Pollutants Weather Sex Factors Female Particulate Matter Infant, Newborn Environmental Exposure Risk Factors Adult Incidence Humans Male Child, Preschool Beijing Aged Middle Aged Deep Learning Child Respiratory Tract Diseases Aged, 80 and over Infant China Young Adult Adolescent
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