The present study shows that naturally the enormous engineering structure interaction with medium material, geometry or non linearity hazardous simulation experiment, response analysis and computing theory have been r...The present study shows that naturally the enormous engineering structure interaction with medium material, geometry or non linearity hazardous simulation experiment, response analysis and computing theory have been regarded as a high level question in the architecture, bridge, tunnel, hydraulic, etc engineering fields.Approaches an integrated intelligent methodology to predict stability and supporting decision in underground drift based on neural network modelling on coal rock mechanical problem is proposed.By the terms of the non linearity numerical simulation, this paper develops integrated intelligent methodology to research on the structure hazardous response strata soft rock drifts.展开更多
A problem of a hierarchy structure optimization is considered.Hierarchical structures arewidely used in the Analytic Hierarchy Process,conjoint analysis,and various other methods of multiplecriteria decision making.Th...A problem of a hierarchy structure optimization is considered.Hierarchical structures arewidely used in the Analytic Hierarchy Process,conjoint analysis,and various other methods of multiplecriteria decision making.The problem consists in finding a structure that needs a minimum number ofpair comparisons for a given total number of the alternatives.For an optimal hierarchy,the minimumefforts are needed for eliciting data and synthesizing the local preferences across the hierarchy to getthe global priorities or utilities.Special estimation techniques are developed and numerical simulationsperformed.Analytical and numerical results suggest optimal ways of priority evaluations for practicalmanagerial decisions in a complex environment.展开更多
Generalized linear mixed models(GLMMs)have been widely used in contemporary ecology studies.However,determination of the relative importance of collinear predictors(i.e.fixed effects)to response variables is one of th...Generalized linear mixed models(GLMMs)have been widely used in contemporary ecology studies.However,determination of the relative importance of collinear predictors(i.e.fixed effects)to response variables is one of the challenges in GLMMs.Here,we developed a novel R package,glmm.hp,to decompose marginal R2^(2)explained by fixed effects in GLMMs.The algorithm of glmm.hp is based on the recently proposed approach‘average shared variance’i.e.used for multivariate analysis.We explained the principle and demonstrated the use of this package by simulated dataset.The output of glmm.hp shows individual marginal R2^(2)s that can be used to evaluate the relative importance of predictors,which sums up to the overall marginal R2^(2).Overall,we believe the glmm.hp package will be helpful in the interpretation of GLMM outcomes.展开更多
文摘The present study shows that naturally the enormous engineering structure interaction with medium material, geometry or non linearity hazardous simulation experiment, response analysis and computing theory have been regarded as a high level question in the architecture, bridge, tunnel, hydraulic, etc engineering fields.Approaches an integrated intelligent methodology to predict stability and supporting decision in underground drift based on neural network modelling on coal rock mechanical problem is proposed.By the terms of the non linearity numerical simulation, this paper develops integrated intelligent methodology to research on the structure hazardous response strata soft rock drifts.
文摘A problem of a hierarchy structure optimization is considered.Hierarchical structures arewidely used in the Analytic Hierarchy Process,conjoint analysis,and various other methods of multiplecriteria decision making.The problem consists in finding a structure that needs a minimum number ofpair comparisons for a given total number of the alternatives.For an optimal hierarchy,the minimumefforts are needed for eliciting data and synthesizing the local preferences across the hierarchy to getthe global priorities or utilities.Special estimation techniques are developed and numerical simulationsperformed.Analytical and numerical results suggest optimal ways of priority evaluations for practicalmanagerial decisions in a complex environment.
基金This work was supported by the National Natural Science Foundation of China(32271551)the Metasequoia funding of Nanjing Forestry University.Conflict of interest statement.The authors declare that they have no conflict of interest.
文摘Generalized linear mixed models(GLMMs)have been widely used in contemporary ecology studies.However,determination of the relative importance of collinear predictors(i.e.fixed effects)to response variables is one of the challenges in GLMMs.Here,we developed a novel R package,glmm.hp,to decompose marginal R2^(2)explained by fixed effects in GLMMs.The algorithm of glmm.hp is based on the recently proposed approach‘average shared variance’i.e.used for multivariate analysis.We explained the principle and demonstrated the use of this package by simulated dataset.The output of glmm.hp shows individual marginal R2^(2)s that can be used to evaluate the relative importance of predictors,which sums up to the overall marginal R2^(2).Overall,we believe the glmm.hp package will be helpful in the interpretation of GLMM outcomes.
