Traditional statistical as well as artificial intelligence techniques are widely used for stock
market forecasting. Due to the nonlinearity in stock data, a model developed using the …

Electronic journal (e-journal) management comprises several aspects, specifically
pageviews, sessions, visitors, and new visitors. Sessions or the number of unique visitors …

In this paper, hybrid methods are proposed to predict OPEC crude oil. In the pre-processing
step, the wavelet decomposition has been used to reduce the noise of time series, which …

Natural gas, known as the cleanest fossil fuel, plays a vital role in the economies of
producing and consuming countries. Understanding and tracking the drivers of natural gas …

This paper presents a Nonlinear Autoregressive Exogenous (NARX) model using feed-
forward neural network learning to forecast the exchange rate. We have evaluated the …

This chapter explores regression techniques with two regression ensemble technique
LSBoosting and Bagging for various time series data: Indian stock market prediction …

In this study, we develop a predictive model using two Machine Learning (ML) techniques:
Artificial Neural Network (ANN) and Deep Learning (DL) architecture called Long Short …