Abstract Gradient Boosted Decision Trees (GBDT's) are a powerful tool for classification and
regression tasks in Big Data. Researchers should be familiar with the strengths and …

The challenges for sustainable cities to protect the environment, ensure economic growth,
and maintain social justice have been widely recognized. Along with the digitization …

Municipalities are increasingly acknowledging the importance of urban form interventions
that can reduce intra-city car travel in achieving more sustainable cities. Current academic …

In-time perception of changing geological conditions is crucial for safe and efficient TBM
tunneling. Precisely detecting or predicting the rock mass qualities ahead of the tunnel face …

Dockless bike-sharing is an effective solution for the metro's first-and last-mile connections.
To create a more bicycle-friendly environment, there is a need to accurately predict the use …

Commuting flow prediction is a crucial issue for transport optimization and urban planning.
However, the two existing types of solutions have inherent flaws. One is traditional models …

Urban network analytics has become an essential tool for understanding and modeling the
intricate complexity of cities. We introduce the Urbanity data repository to nurture this …

Urban networks play a vital role in connecting multiple urban components and developing
our understanding of cities and urban systems. Despite the significant progress we have …

Due to the size of the data involved, performance is an important consideration in the task of
detecting fraudulent Medicare insurance claims. We evaluate CatBoost and XGBoost on the …

I ask whether machine learning (ML) algorithms improve the efficiency in lending without
compromising on equity in a credit environment where soft information dominates. I obtain …