Ensuring accurate estimation of evaporation is weighty for effective planning and judicious management available water resources agricultural practices. Thus, this work enhances the potential support vector regression (SVR) optimized with a novel nature-inspired algorithm, namely, Slap Swarm Algorithm (SVR-SSA) against Whale Optimization (SVR-WOA), Multi-Verse Optimizer (SVR-MVO), Spotted Hyena...

In this article, a PSO-SVR-GRNN nonparametric hybrid model is proposed for the CSI 300 stock index to forecast problem. Particle Swarm Optimization (PSO) utilized optimize parameters of SVR enhance prediction ability support vector machine's regression original Index time series. The optimized residual sequence results General Regression Neural Network (GRNN) are then used series prediction. ou...

Mutations in several subgenomic regions of hepatitis C virus (HCV) have been implicated in influencing the response to interferon (IFN) therapy. Sequences within HCV NS5A (PKR binding domain [PKRBD], IFN sensitivity-determining region [ISDR], and variable region 3 [V3]) were analyzed for the pretreatment serum samples of 60 HCV genotype 1-infected patients treated with pegylated IFN plus ribavi...

BACKGROUND/AIMS A combination of peginterferon and ribavirin is the standard therapy for chronic hepatitis C (CHC). However, the respective study has not been carried out in a large scale in Korea. The purpose of this study was to collect the studies that have been reported in Korea in order to analyze the therapeutic effect of combination therapy and compare to find racial difference. METHOD...

Support Vector Regression (SVR) solves regression problems based on the concept of Support Vector Machine (SVM). In this paper, a new model of SVR with probabilistic constraints is proposed that any of output data and bias are considered the random variables with uniform probability functions. Using the new proposed method, the optimal hyperplane regression can be obtained by solving a quadrati...

This paper investigates the use of ensemble of predictors in order to improve the performance of spatial prediction methods. Support vector regression (SVR), a popular method from the field of statistical machine learning, is used. Several instances of SVR are combined using different data sampling schemes (bagging and boosting). Bagging shows good performance, and proves to be more computation...

In this paper we explore using the support vector regression (SVR) based on the statistics-learning theory of structural risk minimization for the regional logistics demand. Aiming at the blindness of man made choice of parameter and kernel function of SVR, we apply a chaos optimization method to select parameters of SVR. The proposed approach is used for forecasting logistics demand of Shangha...

BACKGROUND Single nucleotide polymorphisms (SNPs) of interleukin-28B (IL28B) have received considerable interest for their association with sustained virological response (SVR) when treating patients of genotype-1 hepatitis C virus (GT1-HCV) chronic infection with pegylated interferon and ribavirin (PegIFN/RBV). This study was to investigate the predictive power of IL28B SNPs for on-treatment r...

BACKGROUND Chronic hepatitis C virus (HCV) infection leads to life-threatening complications worldwide. Immunomodulation signals the response to virus clearance. The immune-suppressive molecule human leukocyte antigen-G (HLA-G) has been shown to function in inhibiting both innate and adaptive immune responses. The objective of this study was to investigate the expression of HLA-G and IL-37 in s...

Systemic vascular resistance (SVR) is a frequently used clinical index of left ventricular afterload. However, SVR may not adequately assess left ventricular afterload (i.e., ventricular internal fiber load during systole) since it reflects only peripheral vasomotor tone. In contrast, left ventricular end-systolic wall stress (sigma es) reflects the combined effects of peripheral loading condit...