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The proposed method is built on a number of propositions.
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The method is built on a classical theory.
The repetitive process of the MCs method is built on the random sampling and statistical analysis.
Our base method is built on a monotone high-resolution Godunov method, the piece-wise parabolic method (PPM).
The proposed method is used to build the knowledge base of that event.
The proposed method is based on an adaptive predictor for the stock price, built from an implicit integration formula.
The proposed method is based on two assumptions.
Our proposed method is developed based on this assumption.
In continue the result of applying the proposed method is presented and it is compared by some other conventional methods based on accuracy, sensitivity and specificity of the classifier which is built on selected genes.
The comparative study, conducted using both simulated and real data, on maps built from real data available in the public domain clearly establish that the proposed method is more accurate, robust and efficient than the other methods.
Based on Theil index, the displacement balanced degree evaluation method is built.
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