Time series forecasting has become a very intensive field of research, which is even
increasing in recent years. Deep neural networks have proved to be powerful and are …

In recent years, deep learning techniques have outperformed traditional models in many
machine learning tasks. Deep neural networks have successfully been applied to address …

Deep learning based forecasting methods have become the methods of choice in many
applications of time series prediction or forecasting often outperforming other approaches …

Deep Learning has been successfully applied to many application domains, yet its
advantages have been slow to emerge for time series forecasting. For example, in the well …

A time series is a sequence of time-ordered data, and it is generally used to describe how a
phenomenon evolves over time. Time series forecasting, estimating future values of time …

Deep learning, one of the most remarkable techniques of machine learning, has been a
major success in many fields, including image processing, speech recognition, and text …

Financial time series forecasting is undoubtedly the top choice of computational intelligence
for finance researchers in both academia and the finance industry due to its broad …

This paper presents a method based on deep learning to deal with big data times series
forecasting. The deep feed forward neural network provided by the H2O big data analysis …

In order to approximate the underlying process of temporal data, time series prediction has
been a hot research topic for decades. Developing predictive models plays an important role …

Deep learning methods offer a lot of promise for time series forecasting, such as the
automatic learning of temporal dependence and the automatic handling of temporal …