Advances of four machine learning methods for spatial data handling: A review
Simultaneous feature selection and support vector machine optimization using the grasshopper optimization algorithm
Support vector machine (SVM) is considered to be one of the most powerful learning
algorithms and is used for a wide range of real-world applications. The efficiency of SVM …
algorithms and is used for a wide range of real-world applications. The efficiency of SVM …
Evaluation of different machine learning models for predicting and map** the susceptibility of gully erosion
Gully erosion constitutes a serious problem for land degradation in a wide range of
environments. The main objective of this research was to compare the performance of seven …
environments. The main objective of this research was to compare the performance of seven …
A support vector machine for landslide susceptibility map** in Gangwon Province, Korea
In this study, the support vector machine (SVM) was applied and validated by using the
geographic information system (GIS) in order to map landslide susceptibility. In order to test …
geographic information system (GIS) in order to map landslide susceptibility. In order to test …
Incorporating spatial autocorrelation in machine learning models using spatial lag and eigenvector spatial filtering features
Applications of machine-learning-based approaches in the geosciences have witnessed a
substantial increase over the past few years. Here we present an approach that accounts for …
substantial increase over the past few years. Here we present an approach that accounts for …
Environmental data science
Environmental data are growing in complexity, size, and resolution. Addressing the types of
large, multidisciplinary problems faced by today's environmental scientists requires the …
large, multidisciplinary problems faced by today's environmental scientists requires the …
[HTML][HTML] Machine learning for predictions of road traffic accidents and spatial network analysis for safe routing on accident and congestion-prone road networks
Y Berhanu, D Schröder, BT Wodajo, E Alemayehu - Results in Engineering, 2024 - Elsevier
Road traffic accidents (RTAs) and the resulting traffic congestion are global concerns mainly
in metropolitan environments. The need for road safety is directly correlated with the rapidly …
in metropolitan environments. The need for road safety is directly correlated with the rapidly …
Optimized green infrastructure planning at the city scale based on an interpretable machine learning model and multi-objective optimization algorithm: A case study of …
Green infrastructure (GI) has developed as a sustainable approach to the mitigation of urban
floods. While machine learning (ML) models have exhibited advantages in urban flood …
floods. While machine learning (ML) models have exhibited advantages in urban flood …