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Wang, X.Y. and Wang, Z.O. (2002) Stock Market Time Series Data Mining Based on Regularized Neural Network and Rough Set. Proceedings of International Conference on Machine Learning and Cybernetics, 1, 315-318.

has been cited by the following article:

• TITLE: Soft Vibrational Force on Stock Market Networks

  AUTHORS: Mehmet Ali Balci, Ömer Akgüller

  KEYWORDS: Network Modelling, Multivariate Analysis, Soft Analysis, Stock Exchange Network, Soft Set Theory

  JOURNAL NAME: Open Access Library Journal, Vol.3 No.10, October 17, 2016

  ABSTRACT: Stock market networks commonly involve uncertainty, and the theory of soft sets emerges as a powerful tool to handle it. In this study, we present a soft analogue of the differential of a vibrational potential function acting on a stock market network as vibrational force. For this purpose, we first study the vibrational potential function operating on each vertex by using the Laplacian of the neighborhood graph, then applied the soft approximator for the soft sets where the data points are embedded to Euclidean n space. We used the data of the globally operating leading stock markets of 17 countries and presented the results respect to them.