Abstract The Shibangou gold deposit in western Henan is associated with irregular quartz veinlets occurring in altered shear zones dissecting a dioritic intrusion. The altered shear zones are characterized by silicifi...Abstract The Shibangou gold deposit in western Henan is associated with irregular quartz veinlets occurring in altered shear zones dissecting a dioritic intrusion. The altered shear zones are characterized by silicification, pyritization, sericilization, chloritization and K-feldspar alteration. Zoning of altered rocks adjacent to the Au-bearing quartz veins is obviously exhibited. Fine-grained sulphides and quartz veinlets of different ages and small-scale fissures are widely distributed in the central part of the altered zones. Major mineralization types in this gold deposit are Au-bearing quartz veinlets and altered rocks in the shear zones. Samples were collected from drilling cores according to the alteration zoning and mineralization type and all samples were analyzed for major and trace elements. Mass balance, volume change (fv=97.3–71.9%) and major element variation sequences are studied in terms of major elements. The changes of mobile components (SiO2, K2O, Fe2O3) and CaO) and immobile component (Al2O3) in the wall-rock alteration are discussed. The gold mineralization is associated with the enrichment of As, Ag, Hg and Pb and depletion of Cu and Zn. The study of compositional variation of altered rocks proves to be a very efficient method for defining the extent of wall-rock alteration, fluid activity and mineralization and enrichment.展开更多
In order to improve the prediction accuracy of compressive strength of concrete,103 groups of concrete data were collected as the samples.We selected seven kinds of ingredients from the concrete samples, using Grid-SV...In order to improve the prediction accuracy of compressive strength of concrete,103 groups of concrete data were collected as the samples.We selected seven kinds of ingredients from the concrete samples, using Grid-SVM, PSO-SVM, and GA-SVM models to establish the prediction model of cubic meter compressive strength of concrete.The experimental results show that SVM model based on Grid optimization algorithm,SVM model based on Particle swarm optimization algorithm,SVM model based on Genetic optimization algorithm mean square error respectively are 0.001, 0.489 8, and 0.304 2, correlation coefficients are 0.994 8, 0.994 6, and 0.993 0. It is shown that cubic meter compressive strength prediction method based on Grid-SVM model is the best optimization algorithm.展开更多
文摘Abstract The Shibangou gold deposit in western Henan is associated with irregular quartz veinlets occurring in altered shear zones dissecting a dioritic intrusion. The altered shear zones are characterized by silicification, pyritization, sericilization, chloritization and K-feldspar alteration. Zoning of altered rocks adjacent to the Au-bearing quartz veins is obviously exhibited. Fine-grained sulphides and quartz veinlets of different ages and small-scale fissures are widely distributed in the central part of the altered zones. Major mineralization types in this gold deposit are Au-bearing quartz veinlets and altered rocks in the shear zones. Samples were collected from drilling cores according to the alteration zoning and mineralization type and all samples were analyzed for major and trace elements. Mass balance, volume change (fv=97.3–71.9%) and major element variation sequences are studied in terms of major elements. The changes of mobile components (SiO2, K2O, Fe2O3) and CaO) and immobile component (Al2O3) in the wall-rock alteration are discussed. The gold mineralization is associated with the enrichment of As, Ag, Hg and Pb and depletion of Cu and Zn. The study of compositional variation of altered rocks proves to be a very efficient method for defining the extent of wall-rock alteration, fluid activity and mineralization and enrichment.
基金Funded by Natioanl Natural Science Foundation of Chin a(Nos.2012BAJ11B00,41301588,41471339,41571514)the Center for Materials Research and Analysis,Wuhan University of Technology
文摘In order to improve the prediction accuracy of compressive strength of concrete,103 groups of concrete data were collected as the samples.We selected seven kinds of ingredients from the concrete samples, using Grid-SVM, PSO-SVM, and GA-SVM models to establish the prediction model of cubic meter compressive strength of concrete.The experimental results show that SVM model based on Grid optimization algorithm,SVM model based on Particle swarm optimization algorithm,SVM model based on Genetic optimization algorithm mean square error respectively are 0.001, 0.489 8, and 0.304 2, correlation coefficients are 0.994 8, 0.994 6, and 0.993 0. It is shown that cubic meter compressive strength prediction method based on Grid-SVM model is the best optimization algorithm.
