In recent years, graphics processing units have made parallel processing affordable with the price of personal desktop computers. This report investigates the computational aspects of calculating simple moving average and exponential moving average operations, two of the most popular financial indicators. In this report, we also investigate the usage of GPU to run artificial neural network as a...

The globalization in market, foreign investment and effect of current news issues makes difficult for investor to take better decisions. This paper introduces a new algorithm CII and describes the process of finding best association rules which is promising one to forecast the market. This experimental work reduces the time required for processing huge stock data and extract best rules with min...

magnetotelluric (mt) method is an important passive surface geophysical method which uses the earth’s natural electromagnetic fields to investigate the electrical resistivity structure of the subsurface. the depth of investigation of mt is much higher than that of other electromagnetic (em) methods (vozoff, 1991). for a general conductivity distribution in the earth, the horizontal electric fie...

In industry, in order to store the reams of data that are collected from all the different flow, level, and temperature sensors, the fast-sampled data are very often downsampled before being stored in a data historian. This downsampled or even compressed data are, then, used by process engineers to recover the appropriate process parameters. However, little has been written about the effects of...

In light of recent research that has begun to examine the link between textual “big data” and social phenomena such as stock price increases, this chapter takes a novel approach to treating news as big data by proposing the intelligent investment decision-making support model based on opinion mining. In an initial prototype experiment, the researchers first built a stock domain-specific sentime...

We propose a neuro-genetic daily stock prediction model. Traditional indicators of stock prediction are utilized to produce useful input features of neural networks. The genetic algorithm optimizes the neural networks under a 2D encoding and crossover. To reduce the time in processing mass data, a parallel genetic algorithm was used on a Linux cluster system. It showed notable improvement on th...

Analyzing big data sets as they occur in modern business and science applications requires query languages that allow for the specification of complex data processing tasks. Moreover, these ideally declarative query specifications have to be optimized, parallelized and scheduled for processing on massively parallel data processing platforms. This paper demonstrates the application of Stratosphe...