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...

The paper investigates the impact of jumps in forecasting co-volatility, accommodating leverage effects. We modify the jump-robust two time scale covariance estimator of Boudt and Zhang (2013) such that the estimated matrix is positive definite. Using this approach we can disentangle the estimates of the integrated co-volatility matrix and jump variations from the quadratic covariation matrix. ...

This paper investigates the predictive ability of financial variables for real growth in the euro area through bivariate and multivariate non-parametric Granger causality tests. Apart from assessing the within-country forecasting ability of commonly-employed financial variables, such as the term spread, the stock market returns and the growth of real money supply, we also test for cross-country...

Precision feeding and management of growing-finishing pigs typically require mathematical models to forecast individual pig performance from past data. The current approaches, namely double exponential smoothing (DES) dynamic linear regression are likely have some limitations in their applicability since they: (1) assume that responses can be forecasted linearly, which only holds the short-term...

Forecasts of agricultural production and prices are intended to be useful for farmers, governments, and agribusiness industries. Because of the special position of food production in a nation’s security, governments have become both principal suppliers and main users of agricultural forecasts. They need internal forecasts to execute policies that provide technical and market support for the agr...

Near-term, ecological forecasting with iterative model refitting and uncertainty partitioning has great promise for improving our understanding of processes the predictive skill models, but to date been infrequently applied predict biogeochemical fluxes. Bubble fluxes methane (CH 4 ) from aquatic sediments atmosphere (ebullition) dominate freshwater greenhouse gas emissions, it remains unknown ...

Since the outbreak of Coronavirus Disease 2019 (COVID-19), spread epidemic has been a major international public health issue. Hence, various forecasting models have used to predict infectious disease. In general, problems often involve prediction accuracy decreasing as horizon increases. Thus, extend without performance or prediction, this study developed Dual Long Short-Term Memory (LSTM) wit...

Bank of Canada working papers are theoretical or empirical works-in-progress on subjects in economics and finance. The views expressed in this paper are those of the author. No responsibility for them should be attributed to the Bank of Canada. Abstract We investigate the macroeconomic determinants of corporate spreads using a no-arbitrage technique. Structural shocks are identified by a New-Ke...