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Liu Y.,Guangdong University of Finance
Computers and Mathematics with Applications | Year: 2013

In this paper, we determine a lower bound for the blow-up time of the nonlinear nonlocal porous medium equation under Robin boundary condition if the solution blows up. The conditions which ensure that the blow-up does not occur are also presented. © 2013 Elsevier Ltd. All rights reserved.

Liu Y.,Guangdong University of Finance | Reissig M.,TU Bergakademie Freiberg
Mathematical Methods in the Applied Sciences | Year: 2014

The goal of the paper is to study the Cauchy problem for 1D models of thermodiffusion. We explain qualitative properties of solutions. In particular, we show which part of the model has a dominant influence on well-posedness, propagation of singularities, Lp-Lq decay estimates on the conjugate line, and on the diffusion phenomenon. Copyright © 2013 John Wiley & Sons, Ltd. Copyright © 2013 John Wiley & Sons, Ltd.

Xiao G.,Guangdong University of Finance
International Journal of Advancements in Computing Technology | Year: 2011

The aim of this paper is to investigate the multiple attribute decision making problems to deal with supplier selection with intuitionistic trapezoidal fuzzy information, in which the information about attribute weights is completely known, and the attribute values take the form of intuitionistic trapezoidal fuzzy number. We developed a multiple attribute decision making method by closeness to ideal alternative in intuitionistic trapezoidal fuzzy setting. Then, we calculate the distances between the ideal alternative and all alternatives to determine the ranking of all alternatives. Finally, an example with supplier selection is given.

Xiao G.,Guangdong University of Finance
International Review on Computers and Software | Year: 2011

The securities customer relationship management system requires a recommend function by exploring the user's behaviors. Personalized recommendation can help people to find interesting things. Rating-based collaborative filtering is the process of predicting how a user would rate a given item from other users. In this paper, Slope one algorithm was initially introduced into the securities keywords recommendation and the feedback of the recommendation result will be use for self learning rating. The goal is to find how a user would rate a given keyword from other user's ratings, that is to say, we should calculate the points of the user for a keyword. We propose a personalized recommendation method joins weighted slope one algorithm and Apriori algorithm, which will improve the calculation accuracy and reduce the computational complexity. We demonstrate the usefulness of the method on a securities dataset. The method has been proved to be useful for obtaining a good recommendation of securities keywords. © 2011 Praise Worthy Prize S.r.l. - All rights reserved.

Luo G.,Guangdong University of Finance
Journal of the Franklin Institute | Year: 2014

We consider robust optimization equilibrium for the bimatrix game based on robust optimization method. In this paper, each player may neither exactly estimate his opponent's strategies nor evaluate his own cost matrix accurately while may estimate a bounded uncertain set. We obtain that the robust optimization equilibrium problem can be formulated as a mixed complementarity problem (MCP) under l1 l∞-norm. Some numerical examples are presented to illustrate the behavior of robust optimization equilibrium. © 2013 The Franklin Institute.

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