in this paper, a novel hybrid model based on neural network and game theory is proposed to support the analyzers in oil market. in this model, first the neural network is utilized to learn the oil prices associated with opec production level and usa imports level. then the learned neural network is applied by a game model. finally the nash equilibrium points of the game present the optimum deci...

Performance stability is an essential feature for the widespread adoption of multicomputers. In this paper, we report the preliminary steps of our research in performance prediction and extrapolation. Performance tuning, guided by extrapolation, may help achieve a substantial fraction of peak performance rates across a broader range of applications while providing guidance for code porting. We ...

Algorithmic information theory gives an idealized notion of compressibility, that is often presented as an objective measure of simplicity. It is suggested at times that Solomonoff prediction, or algorithmic information theory in a predictive setting, can deliver an argument to justify Occam’s razor. This paper explicates the relevant argument, and, by converting it into a Bayesian framework, r...

We consider statistical aspects of the modelling and prediction theory of time series in one and many dimensions. We discuss Lévy-based and general models, and the stationary and non-stationary cases. Our starting point is the recent pair of surveys, Szegö’s theorem and its probabilistic descendants and Multivariate prediction and matrix Szegö theory, by this author.

The aim of this research essay is to examine the structural nature of theory in information systems. Despite the importance of theory, questions relating to its form and structure are neglected in comparison with questions relating to epistemology. The essay addresses issues of causality, explanation, prediction and generalization that underlie an understanding of theory. A taxonomy is proposed...

Current unsteady multi-field simulation data-sets consist of millions of data-points. To efficiently reduce this enormous amount of information, local statistical complexity was recently introduced as a method that identifies distinctive structures using concepts from information theory. Due to high computational costs this method was so far limited to 2D data. In this paper we propose a new st...

With more and more reservoirs have been and are being built all over the world, reservoir-induced earthquake has received a great deal of attention from geoscientists mainly because of its potential to damage constructions and to cause human losses. Based on the previous researches on the environmental conditions of reservoir-induced earthquake, a criteria hierarchy model has been constructed. ...