Scaling industrial applications for the Big Data era

Abstract

Industrial applications tend to rely increasingly on large datasets for regular operations. In order to facilitate that need, we unite the increasingly available hardware resources with fundamental problems found in classical algorithms. We show solutions to the following problems: power flow and island detection in power networks, and the more general graph sparsification. At their core lie respectively algorithms for solving systems of linear equations, graph connectivity and matrix multiplication, and spectral sparsification of graphs, which are applicable on their own to a far greater spectrum of problems. The novelty of our approach lies in developing the first open source and distributed solutions, capable of handling large datasets. Such solutions constitute a toolkit, which, aside from the initial purpose, can be used for the development of unrelated applications and for educational purposes in the study of distributed algorithms.

CBISI-LSTM Deep Learning Model for Short-term Cross-border Capital Flow Prediction

“…There are, however, few studies on the influence of international investor attitudes on international capital flow in the capital market and international capital forecasting. Additionally, as smart devices become more and more popular, more and more people use them for investment-related activities, which increases the amount of data generated and the demand for it [5], both of which have a beneficial effect on the measurement of crossborder investor sentiment. Using this data as a starting point, this paper aims to quantify the sentiment of Chinese cross-border investors following the opening of the SHKSC, in order to construct the sentiment index of cross-border investment and conduct extensive research on the relationship between cross-border investor sentiment and cross-border capital flow as well as the prediction of cross-border capital flow, and observe the impact of cross-border capital sentiment index on the predictability of cross-border capital flow.…”