background despite significant advances in the treatment of chronic hepatitis c in the past decades, factors which can affect response rates to combination therapy; peginterferon and ribavirin, are still under study and reaching sustained virological response (svr) is affected by several different factors. objectives to investigate predictor factors contributing to svr in iranian patients. pati...

In this paper, robust fuzzy neural networks (FNNs) are proposed to identify chaotic systems. In the proposed FNNs, integrating support vector regression (SVR) and annealing robust time-varying learning algorithm (ARTVLA) is adopted to optimize the structure of neural networks. In the evolutionary procedure, first, SVR is adopted to determine the number of hidden layer nodes and the initial stru...

This paper presents dynamic available transfer capability (DATC) determination in power system restructuring environment using support vector regression (SVR). Dynamic available transfer capability is first determined based on the conventional method of potential energy boundary surface transient energy function. Simulations were carried out on a WSCC 3-machine 9-bus system and a Practical Sout...

Support Vector Regression (SVR) is a kernel based regression method capable of implementing a variety of regularisation techniques. Implementation of SVR usually follows a dual optimisation technique which includes Vapnik's -insensitive zone. The number of terms in the resulting SVR approximation function is dependent on the size of this zone, but improving sparsity by increasing the size of th...

The recent Sparse Voronoi Refinement (SVR) Algorithm for mesh generation has the fastest theoretical bounds for runtime and memory usage. We present a robust practical software implementation of the SVR for meshing a piecewise linear complex in 3 dimensions. Our software is competitive in runtime with state of the art freely available packages on generic inputs, and on pathological worse cases ...

In [1], with the evidence framework, the almost inversely linear dependency between the optimal parameter r in norm-r support vector regression machine r-SVR and the Gaussian input noise is theoretically derived. When r takes a non-integer value, r-SVR cannot be easily realized using the classical QP optimization method. This correspondence attempts to achieve two goals: (1) The Newton-decent-m...

The recent Sparse Voronoi Refinement (SVR) Algorithm for mesh generation has the fastest theoretical bounds for runtime and memory usage. We present a robust practical software implementation of the SVR for meshing a piecewise linear complex in 3 dimensions. Our software is competitive in runtime with state of the art freely available packages on generic inputs, and on pathological worse cases ...

Inherent process and measurement uncertainty has posed a challenging issue on soft sensor development of batch bioprocesses. In this paper, a new soft sensor modeling framework is proposed by integrating Bayesian inference strategy with two-stage support vector regression (SVR) method. The Bayesian inference procedure is first designed to identify measurement biases and misalignments via poster...

Precise forecast of the electrical load plays a highly significant role in the electricity industry and market. It provides economic operations and effective future plans for the utilities and power system operators. Due to the intermittent and uncertain characteristic of the electrical load, many research studies have been directed to nonlinear prediction methods. In this paper, a hybrid predi...

Authors have reported conflicting results on the persistence of hepatitis C virus (HCV) infection in patients having sustained virologic response (SVR) to treatment. Therefore, we sought to determine whether chemotherapy leads to viral relapse in 30 HCV-infected patients who had SVR before cancer diagnosis. Half of them had hematologic malignancies. Most (60%) received HCV therapy with interfer...