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Dynamic Space Allocation Based on Internal Demand for Optimizing Release of Shared Parking.

Sensors (Basel, Switzerland)
The size of cities has been continuously increasing because of urbanization. The number of public and private transportation vehicles is rapidly increasing, thus resulting in traffic congestion, traffic accidents, and environmental pollution. Althoug...

A Bibliometric Analysis and Benchmark of Machine Learning and AutoML in Crash Severity Prediction: The Case Study of Three Colombian Cities.

Sensors (Basel, Switzerland)
Traffic accidents are of worldwide concern, as they are one of the leading causes of death globally. One policy designed to cope with them is the design and deployment of road safety systems. These aim to predict crashes based on historical records, ...

Effects of demolishing abandoned buildings on firearm violence: a moderation analysis using aerial imagery and deep learning.

Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention
PURPOSE: Demolishing abandoned buildings has been found to reduce nearby firearm violence. However, these effects might vary within cities and across time scales. We aimed to identify potential moderators of the effects of demolitions on firearm viol...

Analyzing the Check-In Behavior of Visitors through Machine Learning Model by Mining Social Network's Big Data.

Computational and mathematical methods in medicine
The current article paper is aimed at assessing and comparing the seasonal check-in behavior of individuals in Shanghai, China, using location-based social network (LBSN) data and a variety of spatiotemporal analytic techniques. The article demonstra...

Deep learning models to predict flood events in fast-flowing watersheds.

The Science of the total environment
This study aims to explore the reliability of flood warning forecasts based on deep learning models, in particular Long-Short Term Memory (LSTM) architecture. We also wish to verify the applicability of flood event predictions for a river with flood ...

Artificial Intelligence in Geospatial Analysis for Flood Vulnerability Assessment: A Case of Dire Dawa Watershed, Awash Basin, Ethiopia.

TheScientificWorldJournal
This study presents the novelty artificial intelligence in geospatial analysis for flood vulnerability assessment in Dire Dawa, Ethiopia. Flood-causing factors such as rainfall, slope, LULC, elevation NDVI, TWI, SAVI, K-factor, R-factor, river distan...

CNN-Based Spectral Super-Resolution of Panchromatic Night-Time Light Imagery: City-Size-Associated Neighborhood Effects.

Sensors (Basel, Switzerland)
Data on artificial night-time light (NTL), emitted from the areas, and captured by satellites, are available at a global scale in format. In the meantime, data on properties of NTL give more information for further analysis. Such data, however, are...

Applying State-of-the-Art Deep-Learning Methods to Classify Urban Cities of the Developing World.

Sensors (Basel, Switzerland)
This paper shows the efficacy of a novel urban categorization framework based on deep learning, and a novel categorization method customized for cities in the global south. The proposed categorization method assesses urban space broadly on two dimens...

Spatial Prediction of COVID-19 in China Based on Machine Learning Algorithms and Geographically Weighted Regression.

Computational and mathematical methods in medicine
COVID-19 has swept through the world since December 2019 and caused a large number of patients and deaths. Spatial prediction on the spread of the epidemic is greatly important for disease control and management. In this study, we predicted the cumul...

A Novel Smart City-Based Framework on Perspectives for Application of Machine Learning in Combating COVID-19.

BioMed research international
The spread of COVID-19 worldwide continues despite multidimensional efforts to curtail its spread and provide treatment. Efforts to contain the COVID-19 pandemic have triggered partial or full lockdowns across the globe. This paper presents a novel f...