Short‐term traffic forecasting using self‐adjusting k‐nearest neighbours

Short-Term Traffic Forecasting Using Self-Adjusting k-Nearest Neighbours

Short-term traffic forecasting is becoming more important in intelligent transportation systems. The k-nearest neighbours (kNN) method is widely used for short-term traffic forecasting. However, the self-adjustment of kNN parameters has been a problem due to dynamic traffic characteristics. This paper proposes a fully automatic dynamic procedure kNN (DP-kNN) that makes the kNN parameters self-a...

Hoc Retrieval Using KNearest - Neighbors Re -

Internet Traffic Forecasting using Neural Networks [IJCNN1337]

The forecast of Internet traffic is an important issue that has received few attention from the computer networks field. By improving this task, efficient traffic engineering and anomaly detection tools can be created, resulting in economic gains from better resource management. This paper presents a Neural Network Ensemble (NNE) for the prediction of TCP/IP traffic using a Time Series Forecast...

FORECASTING OF TRAFFIC Recommendation E.506 FORECASTING INTERNATIONAL TRAFFIC 1

1 Introduction This Recommendation is the first in a series of three Recommendations that cover international telecommunications forecasting. In the operation and administration of the international telephone network, proper and successful development depends to a large degree upon estimates for the future. Accordingly, for the planning of equipment and circuit provision and of telephone plant ...

Smoothing Using Nearest Neighbours