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Design and optimization of microwave passive components is one of the most critical problems for RF IC designers. However, the state-of-the-art methods either have good efficiency but highly depend on the accuracy of the equivalent circuit models, which may fail the synthesis when the frequency is high; or fully depend on electromagnetic (EM) simulations, whose solution quality is high but are too...
In this paper, we present a new measure of forecast accuracy: a modified mean absolute percentage error (MAPE). As a means of establishing the goodness of fit, we set different objective functions, by implementation of a global optimization algorithm, the results of setting the objective function as modified MAPE are compared with the results of setting the objective function as MAPE, comparisons...
In this paper, we define two new unbiased GM (1, 1) models for the selection of initial conditions: starting-point fixed unbiased GM (1,1) (SUGM (1,1))and ending-point fixed unbiased GM (1, 1) (EUGM (1,1)), which are based on the unbiased GM (1, 1) regarding the 1-th and the n-th vector as the initial condition. Then it gave initial condition an amendment item respectively and carried out an optimization...
Most dynamic optimizers use feedback-directed adaptive optimization techniques. These techniques are expensive because of the profiling overhead. Although the recent trend has been toward the application of machine learning heuristics in compiler optimization, its role in identification and prediction of hotspots has been ignored. This approach evaluates a support vector machine (SVM) based machine...
In this paper, model optimization method of load - bearing capacity of composite foundation based on genetic algorithm is put forward. In this method, the chromosome bit string, which is looked as the generator, is used to complete random combination of influence factor and therefore need not be decoded. Considering both the fitting accuracy to modeling data and prediction accuracy to other data,...
One of the challenging problems in grid environment is the choice of destination nodes where the tasks of the application are to be executed. Therefore, resource prediction is a crucial direction for job scheduling system and grid users. In this paper, Nu-support vector regression (v-SVR) is applied to solve resource prediction problem. The method of parallel multidimensional step search is also introduced...
A method of designing a nonlinear predictive controller based on relational fuzzy model is presented. The fuzzy model is incorporated as a predictor in a nonlinear model - based predictive controller, using internal model control scheme to compensate disturbances and modeling errors. A non-convex optimization problem must be solved at each sampling period. The algorithm is applied to temperature control...
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