Accurate passenger flow prediction is critical for optimizing urban public transportation operations, improving service quality, and reducing passenger waiting times. This study explores the application of three machine learning models—Random Forest (RF), Gradient Boosting Decision Tree (GBDT), and Support Vector Regression (SVR)—in predicting short-term passenger flow of urban bus networks. Using one-month (March 2023) operational... more

Urban energy consumption prediction is critical for Norway’s transition to a low-carbon society, as cities account for 75% of the country’s total energy use. This study applies four machine learning models—XGBoost, LightGBM, CatBoost, and Multilayer Perceptron (MLP)—to predict short-term (24-hour) urban energy consumption in Oslo, using a comprehensive dataset (2022–2023) including meteorological data, building characteristics,... more

Norway’s goal of achieving carbon neutrality by 2050 requires precise monitoring and prediction of urban traffic emissions, a major contributor to national greenhouse gas output. This study applies three machine learning models—Random Forest Regressor (RFR), Gradient Boosting Regressor (GBR), and Artificial Neural Network (ANN)—to predict hourly urban traffic carbon emissions in Bergen, using a 2022–2023... more

This paper focuses on the application of mathematical methods in urban health monitoring, aiming to address challenges such as disease spread prevention, environmental health risk assessment, and public health resource scheduling in urban areas. By integrating graph theory, cluster analysis, and time-series analysis (core mathematical tools in data science), we establish a comprehensive urban health... more

This paper explores the application of mathematical optimization methods (linear programming, genetic algorithms, and graph-based routing) in urban traffic flow management, with a focus on solving congestion mitigation and route efficiency issues in major Romanian cities. Using multi-source traffic data (2021–2023) from Bucharest, Cluj-Napoca, and Iași, we construct a hybrid optimization model that integrates real-time... more