Purpose This study aims to apply a new forecasting approach to improve predictions in the hospitality industry. In order to do so we develop a multivariate setting that allows incorporating the cross-correlations in the evolution of tourist arrivals from visitor markets to a specific destination in Neural Network models. Design/methodology/approach This multiple-input multiple-output approach a...

short-term traffic flow forecasting plays a significant role in the intelligent transportation systems (its), especially for the traffic signal control and the transportation planning research. two mainly problems restrict the forecasting of urban freeway traffic parameters. one is the freeway traffic changes non-regularly under the heterogeneous traffic conditions, and the other is the success...

Wind power has become an important source of power for some countries because wind is renewable, wind power is clean and no pollutants are produced compared to fossil fuels which are mainly used for the generation of energy today. Because of these reasons also in the Netherlands attention towards the use of wind power has grown. In the past decade, a lot of research has been performed on the fo...

In this paper we investigate the impact of data revisions on forecasting and model selection procedures. A linear ARMA model and nonlinear SETAR model are considered in this study. Two Canadian macroeconomic time series have been analyzed: the real-time monetary aggregate M3 (1977-2000), and residential mortgage credit (1975-1998). The forecasting method we use is multistep-ahead non-adaptive f...

Despite the superiority of convolutional neural networks demonstrated in time series modeling and forecasting, it has not been fully explored on design network architecture tuning hyper-parameters. Inspired by incremental construction strategy for building a random multilayer perceptron, we propose novel Error-feedback Stochastic Modeling (ESM) to construct Convolutional Neural Network (ESM-CNN...