Numerous studies have adopted deep learning (DL) in financial market forecasting models
owing to its superior performance. The DL models require as many relevant input variables …

The purpose of this paper is to develop and identify the best hybrid model to predict stock
index returns. We develop three different hybrid models combining linear ARIMA and non …

Currently there is no universal sustainability assessment methodology, which would be
applicable by policy‐makers for identification of regional development paths, policies' …

As the age of Big Data emerges, it becomes necessary to take the five dimensions of Big
Data-volume, variety, velocity, volatility, and veracity-and focus these dimensions towards …

Financial forecasting is an area of research which has been attracting a lot of attention
recently from practitioners in the field of artificial intelligence. Apart from the economic …

In deciding production-plan, material-inventory, scheduling, etcetera of an automobile
industry, the accuracy of forecasting techniques plays a very important role. The quantitative …

Artificial Neural Networks (ANN) have been frequently applied to reduce risks and maximize
the net returns in different types of algorithm trading. Using a real dataset, and aiming to …

A tea packaging company in India was implementing supply chain planning process to
improve its delivery performance. For this purpose the company was interested in …

With the development of China's economy, China's aviation market has expanded, and
related industries have also developed rapidly. For the long-term development of the …

This paper describes a framework that utilizes an adaptive‐network‐based fuzzy inference
system to perform user‐constrained pattern recognition on time‐series data. Using a …