Knowledge of phenological events and their variability can help to determine final yield, plan management approach, tackle climate change, and model crop development. THe timing of phenological stages and phases is known to be highly correlated with ...
Given the ever present threat of vehicular accident occurrence endangering the lives of most people, preventative measures need to be taken to combat vehicle accident occurrence. From dangerous weather to hazardous roadway conditions, there are a hig...
The robust estimate and forecast capability of random forests (RF) has been widely recognized, however this ensemble machine learning method has not been widely used in mosquito-borne disease forecasting. In this study, two sets of RF models were dev...
Journal of environmental sciences (China)
Jun 14, 2020
Surface monitoring, vertical atmospheric column observation, and simulation using chemical transportation models are three dominant approaches for perception of fine particles with diameters less than 2.5 micrometers (PM) concentration. Here we explo...
Risk analysis : an official publication of the Society for Risk Analysis
May 19, 2020
Artificial intelligence (AI) methods have seen increasingly widespread use in everything from consumer products and driverless cars to fraud detection and weather forecasting. The use of AI has transformed many of these application domains. There are...
Providing drivers with real-time weather information and driving assistance during adverse weather, including fog, is crucial for safe driving. The primary focus of this study was to develop an affordable in-vehicle fog detection method, which will p...
Lane change has been recognized as a challenging driving maneuver and a significant component of traffic safety research. Developing a real-time continuous lane change detection system can assist drivers to perform and deal with complex driving tasks...
Computational intelligence and neuroscience
Mar 11, 2020
We propose three quality control (QC) techniques using machine learning that depend on the type of input data used for training. These include QC based on time series of a single weather element, QC based on time series in conjunction with other weat...
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...
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...