[HTML][HTML] Extracting spatial effects from machine learning model using local interpretation method: An example of SHAP and XGBoost

Z Li - Computers, Environment and Urban Systems, 2022 - Elsevier
Abstract Machine learning and artificial intelligence (ML/AI), previously considered black box
approaches, are becoming more interpretable, as a result of the recent advances in …

Parking prediction in smart cities: A survey

X Xiao, Z Peng, Y Lin, Z Jin, W Shao… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
With the growing number of cars in cities, smart parking is gradually becoming a strategic
issue in building a smart city. As the precondition in smart parking, accurate parking …

Short-term traffic flow prediction based on optimized deep learning neural network: PSO-Bi-LSTM

P Redhu, K Kumar - Physica A: Statistical Mechanics and its Applications, 2023 - Elsevier
Traffic flow prediction is important for urban planning and traffic congestion alleviation as
well as for intelligent traffic management systems. Due to the periodic characteristics and …

The challenges of integrating explainable artificial intelligence into GeoAI

J Xing, R Sieber - Transactions in GIS, 2023 - Wiley Online Library
Although explainable artificial intelligence (XAI) promises considerable progress in
glassboxing deep learning models, there are challenges in applying XAI to geospatial …

Classification of white blood cells with SVM by selecting SqueezeNet and LIME properties by mRMR method

E Başaran - Signal, Image and Video Processing, 2022 - Springer
White blood cells, which have an important role in the human immune system, protect the
body against various viruses, harmful bacteria and infections. If there are not enough white …

Efficient and explainable ship selection planning in port state control

R Yan, S Wu, Y Jin, J Cao, S Wang - Transportation Research Part C …, 2022 - Elsevier
Port state control is the safeguard of maritime transport achieved by inspecting foreign
visiting ships and supervising them to rectify the non-compliances detected. One key issue …

Exploring determinants of feeder mode choice behavior using Artificial Neural Network: Evidences from Delhi metro

G Saiyad, M Srivastava, D Rathwa - Physica A: Statistical Mechanics and its …, 2022 - Elsevier
First and last mile connectivity are the most crucial elements of transit system. However,
inadequate attention is given to such issues in developing countries like India. The present …

Explainable Artificial Intelligence for Intelligent Transportation Systems: Are We There Yet?

A Adadi, A Bouhoute - Explainable Artificial Intelligence for …, 2023 - taylorfrancis.com
(AI) and Machine Learning (ML) are set to revolutionize all industries, Intelligent
Transportation Systems (ITS) field is no exception. However, being a safety-critical system …

Predicting households' residential mobility trajectories with geographically localized interpretable model-agnostic explanation (GLIME)

C Jin, S Park, HJ Ha, J Lee, J Kim… - International Journal …, 2023 - Taylor & Francis
Human mobility analytics using artificial intelligence (AI) has gained significant attention with
advancements in computational power and the availability of high-resolution spatial data …

Analysis of taste heterogeneity in commuters' travel decisions using joint parking–and mode–choice model: A case from urban India

J Parmar, G Saiyed, S Dave - Transportation Research Part A: Policy and …, 2023 - Elsevier
In developing countries like India, the policymakers have largely focused on supply-side
measures, yet demand-side measures have remained unaddressed in policy implications …