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A conventional grey Markov model will produce large errors when it's used for the prediction of a sequence with large volatility. These errors can lead to prediction failure. So it is necessary to improve the model. In order to reduce the volatility, the logarithm of the original sequence is firstly calculated, and then the minimum error is used to replace the relative error of the grey model. After...
Understanding input/output (I/O) performance in high performance computing (HPC) is becoming increasingly important as the gap between the performance of computation and I/O widens. In this paper we propose a methodology to predict an application's disk I/O time while running on High Performance Computing Modernization Program (HPCMP) systems. Our methodology consists of the following steps: 1) Characterize...
Ciągłe deformacje powierzchni terenu wywołane podziemną eksploatacją górniczą mogą powodować zagrożenie budynków i infrastruktury. Zagadnienie modelowania deformacji od strony teoretycznej jest znane od wielu lat. Powszechnie stosowany jest model Knothego. Dokładność prognozowanych deformacji zależy w dużej mierze od prawidłowej identyfikacji parametrów modelu i warunków zalegania przewidzianego do...
In this paper the problem of prediction of queue lengths in the multi-queue-single-processor queuing system is considered. Efficient solutions for this problem are crucial in many technical appliances, such as load balancing in multi-processor systems. Here, a fuzzy-neural model for approximation of the average future system load along with model identification algorithm are proposed. Moreover, condition...
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