Abstract Feature selection is a technique used to reduce complexity and improve performance in regards generalization, fit, accuracy of prediction for machine learning models. A central challenge this process that the search over space features find subset k optimal known NP-Hard problem. In work, we study metrics encoding combinatorial as binary quadratic model, such Generalized Mean Informati...

In this paper we simulate the breeding process of marker-assisted introgressing a favorable QTL allele from “donor” to “recipient”. During this process, the foreground selection and background selection were made for introgression population simultaneously: foreground selection is making indirect selection of target gene by its closely linked two flanking markers, four selection methods includi...

pulmonary hypertension syndrome (ascites) is a metabolic disorder in fast-growing broilers. inconsistency of oxygen requirement and the cardiovascular ability make the birds susceptible to ascites. incidence of ascites was accompanied by right ventricular hypertrophy, fluid accumulation in the abdominal cavity and finally mortality. the objective of the current study was to review the genetic b...

Several studies have shown that selection of purebreds for increased performance of their crossbred descendants under field conditions is hampered by low genetic correlations between purebred and commercial crossbred (CC) performance. Although this can be addressed by including phenotypic data from CC relatives for selection of purebreds through combined crossbred and purebred selection (CCPS),...

Molecular marker-assisted selection (MAS) is currently being employed in two areas of rice breeding at the University of Arkansas Rice Research and Extension Center (RREC) in Stuttgart. Presently the objective of the program is to accelerate the development of rice cultivars with improved cooking quality and rice blast disease resistance using two well-characterized molecular markers. A co-domi...

This paper presents methodologies to select equities based on soft-computing models which focus on applying fundamental analysis for equities screening. This paper compares the performance of three soft-computing models, namely multi-layer perceptrons (MLP), adaptive neuro-fuzzy inference systems (ANFIS) and general growing and pruning radial basis function (GGAP-RBF). It studies their computat...