AIMC Topic: Meteorology
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Providing an accurate global model for monthly solar radiation forecasting using artificial intelligence based on air quality index and meteorological data of different cities worldwide.
Environmental science and pollution research international
May 3, 2021
This study aims to present an exact model for predicting solar radiation worldwide through a general model. In this study, mean monthly global solar radiation would have been predicted by applying artificial intelligence methods including artificial ...
Simulating reference crop evapotranspiration with different climate data inputs using Gaussian exponential model.
Environmental science and pollution research international
Mar 30, 2021
Obtaining accurate data on reference crop evapotranspiration (ET) is important for agricultural water management. A novel Gaussian exponential model (GEM) was developed in this study to predict ET with limited climatic data. The GEM was further compa...
Using a deep convolutional neural network to predict 2017 ozone concentrations, 24 hours in advance.
Neural networks : the official journal of the International Neural Network Society
Sep 28, 2019
In this study, we use a deep convolutional neural network (CNN) to develop a model that predicts ozone concentrations 24 h in advance. We have evaluated the model for 21 continuous ambient monitoring stations (CAMS) across Texas. The inputs for the C...
Prediction of environmental effects in received signal strength in FM/TV station based on meteorological parameters using artificial neural network and data mining.
Journal of environmental management
Sep 9, 2019
In this paper, meteorological parameters, electric field strength and transmitters' output power measured during six months in a TV/FM station. There are 13 frequencies in FM and UHF frequency bands in pilot broadcast station. The analysis of results...
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...
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...
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...
Machine learning modeling of plant phenology based on coupling satellite and gridded meteorological dataset.
International journal of biometeorology
Apr 11, 2018
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...
Eyes on our planet.
Current biology : CB
Feb 6, 2018
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...
Evaluating the predictability of PM grades in Seoul, Korea using a neural network model based on synoptic patterns.
Environmental pollution (Barking, Essex : 1987)
Sep 6, 2016
As of November 2014, the Korean Ministry of Environment (KME) has been forecasting the concentration of particulate matter with diameters ≤ 10 μm (PM) classified into four grades: low (PM ≤ 30 μg m), moderate (30 < PM ≤ 80 μg m), high (80 < PM ≤ 150 ...
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