Add to ORKGAn application of time series prediction, to traffic forecasting in ATM networks, using neural nets is described. One key issue, the number of data points needed to be included in the input representation to the net is discussed from a theoretical point of view, and the results are applied in the model under discussion. Experimental results are discussed and analysed
The paper presents the results of building neural network predictive models of the occupancy of the ...
It is possible for routing and navigation applications to provide more accurate and more effective r...
It is possible for routing and navigation applications to provide more accurate and more effective r...
Neural Network approaches to time series prediction are briefly discussed, and the need to specify a...
This article presents three methods to forecast accurately the amount of traffic in TCP=IP based net...
Time series network traffic analysis and forecasting are important for fundamental to many decision-...
Time series network traffic analysis and forecasting are important for fundamental to many decision-...
Time series network traffic analysis and forecasting are important for fundamental to many decision-...
This paper presents a binary neural network algorithm for short-term traffic flow prediction. The al...
This paper presents a binary neural network algorithm for short-term traffic flow prediction. The al...
The dynamics of data traffic intensity is examined using traffic measurements at the interface switc...
Time series data analysis and forecasting tool for studying the data on the use of network traffic i...
By improving Internet traffic forecasting, more efficient TCP/IP traffic control and anomaly detecti...
Time series data analysis and forecasting tool for studying the data on the use of network traffic i...
Abstract: This article presents three methods to forecast accurately the amount of traffic in TCP=IP...
The paper presents the results of building neural network predictive models of the occupancy of the ...
It is possible for routing and navigation applications to provide more accurate and more effective r...
It is possible for routing and navigation applications to provide more accurate and more effective r...
Neural Network approaches to time series prediction are briefly discussed, and the need to specify a...
This article presents three methods to forecast accurately the amount of traffic in TCP=IP based net...
Time series network traffic analysis and forecasting are important for fundamental to many decision-...
Time series network traffic analysis and forecasting are important for fundamental to many decision-...
Time series network traffic analysis and forecasting are important for fundamental to many decision-...
This paper presents a binary neural network algorithm for short-term traffic flow prediction. The al...
This paper presents a binary neural network algorithm for short-term traffic flow prediction. The al...
The dynamics of data traffic intensity is examined using traffic measurements at the interface switc...
Time series data analysis and forecasting tool for studying the data on the use of network traffic i...
By improving Internet traffic forecasting, more efficient TCP/IP traffic control and anomaly detecti...
Time series data analysis and forecasting tool for studying the data on the use of network traffic i...
Abstract: This article presents three methods to forecast accurately the amount of traffic in TCP=IP...
The paper presents the results of building neural network predictive models of the occupancy of the ...
It is possible for routing and navigation applications to provide more accurate and more effective r...
It is possible for routing and navigation applications to provide more accurate and more effective r...