Traffic congestion is a significant problem that adversely affects the economy, environment,
and public health in urban areas worldwide. One promising solution is to forecast road-level …

The accurate prediction of traffic flow has emerged as a focal point in the cutting-edge
sphere of intelligent transportation. Extant methodologies rely on deep learning for short …

Effective traffic congestion prediction is need of the hour in a modern smart city to save time
and improve the quality of life for citizens. In this study, AB_AO (ARIMA Bi‐LSTM using …

Long sequence time-series forecasting (LSTF) is a significant and challenging task. Many
real-world applications require long-term forecasting of time series. In recent years …

The study aims to monitor air pollution in Iranian metropolises using remote sensing,
specifically focusing on pollutants such as O3, CH4, NO2, CO2, SO2, CO, and suspended …

Обґрунтовано структуру математичної моделі оцінки ергономічної стійкості
транспортного потоку на різних ділянках дорожньої мережі при дії зовнішніх збурень …

Scorecard is the main method used by financial institutions to quantitatively assess customer
credit risk. The traditional scorecard mainly uses the logical regression (LR) for modeling …

The challenge of forecasting time series has long been recognized in many industries, and
deep learning has become a widely adopted solution. While prior studies mostly focus on …

Wavelet analysis is an effective manner to estimate community congestion based on time
collection analysis. Wavelet evaluation is an effective sign-processing method that can …

The conventional dynamic tracking method of train number of rail transit signal system
mainly uses the ZG (Zone Controller) regional controller to report the train position, which is …