[HTML][HTML] Machine learning applied to road safety modeling: A systematic literature review
Road safety modeling is a valuable strategy for promoting safe mobility, enabling the
development of crash prediction models (CPM) and the investigation of factors contributing …
development of crash prediction models (CPM) and the investigation of factors contributing …
Quantifying and comparing the effects of key risk factors on various types of roadway segment crashes with LightGBM and SHAP
Understanding and quantifying the effects of risk factors on crash frequency is of great
importance for developing cost-effective safety countermeasures. In this paper, the effects of …
importance for developing cost-effective safety countermeasures. In this paper, the effects of …
Context-aware machine learning for intelligent transportation systems: A survey
Context awareness adds intelligence to and enriches data for applications, services and
systems while enabling underlying algorithms to sense dynamic changes in incoming data …
systems while enabling underlying algorithms to sense dynamic changes in incoming data …
[HTML][HTML] Application of machine learning and genetic optimization algorithms for modeling and optimizing soybean yield using its component traits
Improving genetic yield potential in major food grade crops such as soybean (Glycine max
L.) is the most sustainable way to address the growing global food demand and its security …
L.) is the most sustainable way to address the growing global food demand and its security …
On the interpretability of machine learning methods in crash frequency modeling and crash modification factor development
Abstract Machine learning (ML) model interpretability has attracted much attention recently
given the promising performance of ML methods in crash frequency studies. Extracting …
given the promising performance of ML methods in crash frequency studies. Extracting …
[HTML][HTML] The application of artificial neural networks in modeling and predicting the effects of melatonin on morphological responses of citrus to drought stress
M Jafari, A Shahsavar - Plos one, 2020 - journals.plos.org
Drought stress as one of the most devastating abiotic stresses affects agricultural and
horticultural productivity in many parts of the world. The application of melatonin can be …
horticultural productivity in many parts of the world. The application of melatonin can be …
Safety critical event prediction through unified analysis of driver and vehicle volatilities: Application of deep learning methods
Transportation safety is highly correlated with driving behavior, especially human error
playing a key role in a large portion of crashes. Modern instrumentation and computational …
playing a key role in a large portion of crashes. Modern instrumentation and computational …
Fifty years of accident analysis & prevention: A bibliometric and scientometric overview
Abstract Accident Analysis & Prevention (AA&P) is a leading academic journal established
in 1969 that serves as an important scientific communication platform for road safety studies …
in 1969 that serves as an important scientific communication platform for road safety studies …
A Bayesian spatial random parameters Tobit model for analyzing crash rates on roadway segments
This study develops a Bayesian spatial random parameters Tobit model to analyze crash
rates on road segments, in which both spatial correlation between adjacent sites and …
rates on road segments, in which both spatial correlation between adjacent sites and …
Hybrid soft computing approach based on clustering, rule mining, and decision tree analysis for customer segmentation problem: Real case of customer-centric …
K Khalili-Damghani, F Abdi, S Abolmakarem - Applied Soft Computing, 2018 - Elsevier
This paper proposes a hybrid soft computing approach on the basis of clustering, rule
extraction, and decision tree methodology to predict the segment of the new customers in …
extraction, and decision tree methodology to predict the segment of the new customers in …