This study presents a hybrid approach that integrates seasonal-trend decomposition and
machine learning (termed STL-ML) for predicting the rainfall time series one step ahead …

Forecasting the short-term metro ridership is an important issue for operation management
of metro systems. However, it cannot be solved well by the single long short-term memory …

Network traffic analysis and predictions have become vital for monitoring networks. Network
prediction is the process of capturing network traffic and examining it deeply to decide what …

The prediction of network traffic characteristics helps in understanding this complex
phenomenon and enables a number of practical applications, ranging from network …

Tailings dams are constructed as storage dams for ore waste, serving as industrial waste
piles and for drainage. The dam is negatively affected by rainfall, infiltration lines and its own …

Computer network traffic control is a torrid research topic nowadays, as this task helps in
various applications like anomaly detection, congestion control and bandwidth control …

With the development of networking technologies, global Internet traffic is constantly
increasing. Moreover, various traffic types associated with a variety of network services and …

The practice of predicting the traffic that is headed toward a specific website is known as
web traffic prediction. To govern a network, network traffic forecasting is crucial. Since clients …

Ubiquitous Internet of Things (IoT) sensors in the smart city generate various urban utility
sequential data, such as electricity and water usage records, which are defined as …

The power load prediction is significant in a sustainable power system, which is the key to
the energy system's economic operation. An accurate prediction of the power load can …