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Effectiveness forecast of especial vehicle is important in vehicle development and compare research. This paper establishes forecast model of vehicle effectiveness by factors analysis with interpretability, and RBF (radial basis function) neural networks with short training time and precise function. Secondly, the result of forecasted and original is contrasted together, then the quality and creditability...
Many relational domains contain temporal information and dynamics that are important to model (e.g., social networks, protein networks). However, past work in relational learning has focused primarily on modeling static "snapshots" of the data and has largely ignored the temporal dimension of these data. In this work, we extend relational techniques to temporally-evolving domains and outline...
We present a generic method for analyzing the effect of process variability in nanoscale circuits. The proposed framework uses kernel and a generic tail probability estimator to eliminate the need for a-priori density choice for the nature of circuit variation. This allows capturing the true nature of the circuit variation from a few random samples of its observed responses. The data-driven, non-parametric,...
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