… neural ODEs are implemented in PyTorch and compared … The univariate neural ODE achieved
the lowest average error, … Implementado en R, se sigue la metodología BoxJenkins para …

… Univariate models are applied to the datasets to forecast them based on their … , forecasting
the future in construction market outputs like construction put in place, Construction Cost Index …

… The seasonal ARIMA (SARIMA) model is a variant of these Box-Jenkins time series models
… (BP) neural network for predicting the stock price index. The researchers, then, compared the …

… a tender or reverse auction is in comparison to spot quotations. Thirdly and finally, the section
focuses on rating forecasting ocean freight rates… Freight rates level result on the immediate …

… and Box-Jenkins ARIMA in forecasting electricity price in Port … segmentation, neural techniques
and forecast combinations. … for forecasting electricity prices, also in comparison to earlier …

… material prices, construction costs and construction cost index were top … Artificial Neural
Network (ANN) model could use historical prices, … Comparison of three forecasting models …

… describing and comparing the dynamics of electricity prices for some … , deep neural networks,
convolutional neural networks [18]. … Standard analysis of each series using the Box-Jenkins …

… (eg, neural approach, SVR) for univariate TS forecasting and … and used TS forecasting
approaches to forecast and compared their … Reliability of the Box– Jenkins model for forecasting …

… efficient forecasting models using it for the Wholesale Price Index (WPI) of all the twenty-five
individual items of the manufacture of the textiles group of India. Upon comparison, the …

… to material price and cost index forecasting and demonstrates its … This study compares and
evaluates the relative performance … autocorrelation functions per the Box–Jenkins approach. …