This paper presents a review of the literature on network traffic prediction, while also serving
as a tutorial to the topic. We examine works based on autoregressive moving average …

Network traffic prediction is essential and significant to network management and network
security. Existing prediction methods cannot well capture the temporal–spatial correlations …

The efficient and smooth operation of the transportation system is crucial for ensuring the
normal functioning of modern society and people's daily lives. However, the increase in …

Existing traffic prediction methods are based on previously collected traffic patterns, and the
measured data are used to train and create a model to predict future traffic patterns …

Traditionally, mobile network management has been based on reactive systems, where
corrective actions are taken when a failure or a suboptimal network performance is detected …

Nowadays, multivariate time series data is increasingly collected in many large-scale
application systems, which often has periodic, repetitive patterns that can be affected by …

This paper analyzes vibration data that shows sudden amplitude changes due to non-
stationary load conditions. The data were recorded in a wind turbine that operated under …

Effective resource allocation is a crucial requirement to achieve the stringent performance
targets of ultra-reliable low-latency communication (URLLC) services. Predicting future …

Pepper is one of Lampung's leading export commodities. It can be seen from the
contribution of Lampung Province's pepper, which accounted for 42 percent of Indonesia's …

Deep learning is leading the way of numerous ongoing advances. With sufficient high-
quality training data, correct implementations, and benign training environments, deep …