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This paper is to present a simplified model to estimate aircraft fuel consumption using support vector algorithm. The method developed here can be implemented in fast-time airspace and airfield simulation application. A representative support vector network aided fuel consumption model is developed using data given in the route date and aircraft performance manual, support vector machine is trained...
Although empirical studies have demonstrated the usefulness of statistical fault localizations based on code coverage, the effectiveness of these techniques may be deteriorated due to the presence of some undesired circumstances such as the existence of coincidental correctness where one or more passing test cases exercise a faulty statement and thus causing some confusion to decide whether the underlying...
Protein--protein interaction (PPI) is a major way for proteins to perform their biological functions. Due to the lack of the PPI experimental data, theoretical prediction seems important to understand protein functions. Up to now, there have been various computational methods as for how to predict PPI. This report, however, will present a novel approach to the prediction of PPI by analyzing protein...
We present results from a comparative empirical study of two methods for constructing support vector machines (SVMs). The first method is the conventional one based on the quadratic programming approach, which builds the optimal separating hyperplane maximizing the margin between two classes (SVM-Q). The second method is based on the linear programming approach suggested by Vapnik to build a separating...
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