This paper describes the importance of the RBF model quality in a model-based predictive control scheme. We show that a good neuronal approximator does not necessarily correctly model the intrinsic behaviour of the identified system. We have used a simulated example to show the harmful effects of a particular type of incorrect behaviour, the non-invertibility of the model relative to the contro...

BACKGROUND Epidemiological evidence suggests that vitamin D deficiency is linked to various chronic diseases. However direct measurement of serum 25-hydroxyvitamin D (25(OH)D) concentration, the accepted biomarker of vitamin D status, may not be feasible in large epidemiological studies. An alternative approach is to estimate vitamin D status using a predictive model based on parameters derived...

In order to overcome the separately selection advantages of traditional feature and RBF neural network parameter, increase accuracy rate of network’s intrusion detection, there came up with a research on neural network intrusion detection of improved particle swarm optimization. According to optimize the feature selection of network and RBF neural network parameter, established a neural network...

A new construction algorithm for multi-output radial basis function (RBF) network modelling is introduce by combining a locally regularized orthogonal least squares (LROLS) model selection with a D-optimality experimental design. The proposed algorithm aims to achieve maximized model robustness and sparsity via two effective and complementary approaches. The LROLS method alone is capable of pro...

A construction algorithm for multioutput radial basis function (RBF) network modelling is introduced by combining a locally regularised orthogonal least squares (LROLS) model selection with a D-optimality experimental design. The proposed algorithm aims to achieve maximised model robustness and sparsity via two effective and complementary approaches. The LROLS method alone is capable of produci...

We present a method of modifying the structure of radial basis function (RBF) network to work with nonstationary series that exhibit homogeneous nonstationary behavior. In the original RBF network, the hidden node's function is to sense the trajectory of the time series and to respond when there is a strong correlation between the input pattern and the hidden node's center. This type of respons...

The response surface methodology (RSM), which typically uses quadratic polynomials, is predominantly used for metamodeling in crashworthiness optimization because of the high computational cost of vehicle crash simulations. Research shows, however, that RSM may not be suitable for modeling highly nonlinear responses that can often be found in impact related problems, especially when using limit...

Sensor systems are not always equipped with the ability to track targets. Sudden maneuvers of a target can have a great impact on the sensor system, which will increase the miss rate and rate of false target detection. The use of the generic particle filter (PF) algorithm is well known for target tracking, but it can not overcome the degeneracy of particles and cumulation of estimation errors. ...

Alterations in renal function contribute to Goldblatt two-kidney, one-clip (2K1C) hypertension. A previous study indicated that bioavailability of cytochrome P-450 metabolites epoxyeicosatrienoic acids (EETs) is decreased while that of 20-hydroxyeicosatetraenoic acids (20-HETE) is increased in this model. We utilized the inhibitor of soluble epoxide hydrolase cis-4-[4-(3-adamantan-1-yl-ureido)-...

Alterations in renal function contribute to Goldblatt 2-kidney 1-clip (2K1C) hypertension. A previous study indicated that bioavailability of cytochrome P450 metabolites epoxyeicosatrienoic acids (EETs) is decreased while 20hydroxyeicosatetraenoic acids (20-HETE) is increased in this model. We utilized the inhibitor of soluble epoxide hydrolase cis-4-[4-(3-Adamantan-1-yl-ureido)-cyclohexyloxy]b...