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A LS-SVM based adaptive tracking control approach is presented for a class of unknown nonlinear dynamic systems in this paper. Based on input/output feedback linearization approach, the nonlinear system is transformed into partially linear controllable system. Then the LS-SVM technique is employed to perform approximating unknown nonlinear functions. The updating rule of LS-SVM parameters is derived...
That many domestic corporations have suffered from financial crises recently victimizes shareholders of those corporations and. Prior researches about those financial crises are basically one-dimensional basing on static balance sheets or variables of macroeconomics. The present research is directed to utilizing self-organizing mapping (SOM) of a neural network in the dynamic environment for discovering...
The work condition of automobile engine is terrible, so it has faults frequently. In order to guarantee the normal work of automobile, the intelligence fault diagnosis system has built. Fuzzy neural network technology is applied to the fault diagnosis system. Korean Hyundai GRANDEUR series DOHC engine is the diagnostic object. The test car has eight fault processing modules. Among them the ECU fault...
Data fusion method is applied in fault diagnosis field. The faults are diagnosed through three levels which are data fusion level, feature level and decision level respectively. The feature level uses multi-collateral neural networks. The purpose of using neural networks is mainly getting basic probability assignment (BPA) of D-S evidence theory. On the other hand the neural networks in feature level...
Given a set of trajectories D, a query object (point or trajectory) q, and a query interval T, a mutual (i.e., symmetric) nearest neighbor (MNN) query over trajectories finds from D within T, the set of trajectories that are among the k1 nearest neighbors (NNs) of q, and meanwhile, have q as one of their k2 NNs. This type of queries considers proximity of q to the trajectories and the proximity of...
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