The growth optimizer(GO)is an innovative and robust metaheuristic optimization algorithm designed to simulate the learning and reflective processes experienced by individuals as they mature within the social environme...The growth optimizer(GO)is an innovative and robust metaheuristic optimization algorithm designed to simulate the learning and reflective processes experienced by individuals as they mature within the social environment.However,the original GO algorithm is constrained by two significant limitations:slow convergence and high mem-ory requirements.This restricts its application to large-scale and complex problems.To address these problems,this paper proposes an innovative enhanced growth optimizer(eGO).In contrast to conventional population-based optimization algorithms,the eGO algorithm utilizes a probabilistic model,designated as the virtual population,which is capable of accurately replicating the behavior of actual populations while simultaneously reducing memory consumption.Furthermore,this paper introduces the Lévy flight mechanism,which enhances the diversity and flexibility of the search process,thus further improving the algorithm’s global search capability and convergence speed.To verify the effectiveness of the eGO algorithm,a series of experiments were conducted using the CEC2014 and CEC2017 test sets.The results demonstrate that the eGO algorithm outperforms the original GO algorithm and other compact algorithms regarding memory usage and convergence speed,thus exhibiting powerful optimization capabilities.Finally,the eGO algorithm was applied to image fusion.Through a comparative analysis with the existing PSO and GO algorithms and other compact algorithms,the eGO algorithm demonstrates superior performance in image fusion.展开更多
In view of the composition analysis and identification of ancient glass products, L1 regularization, K-Means cluster analysis, elbow rule and other methods were comprehensively used to build logical regression, cluste...In view of the composition analysis and identification of ancient glass products, L1 regularization, K-Means cluster analysis, elbow rule and other methods were comprehensively used to build logical regression, cluster analysis, hyper-parameter test and other models, and SPSS, Python and other tools were used to obtain the classification rules of glass products under different fluxes, sub classification under different chemical compositions, hyper-parameter K value test and rationality analysis. Research can provide theoretical support for the protection and restoration of ancient glass relics.展开更多
加性分位数回归为非线性关系的建模提供一种灵活、鲁棒的方法.拟合加性分位数模型的方法通常使用样条函数逼近分量,但需要先验的选择节点,计算速度较慢,并不适合大规模数据问题.因此文中提出基于融合Lasso的非参数加性分位数回归模型(No...加性分位数回归为非线性关系的建模提供一种灵活、鲁棒的方法.拟合加性分位数模型的方法通常使用样条函数逼近分量,但需要先验的选择节点,计算速度较慢,并不适合大规模数据问题.因此文中提出基于融合Lasso的非参数加性分位数回归模型(Nonparametric Additive Quantile Regression Model Based on Fused Lasso,AQFL),是在融合Lasso罚和l_(2)罚之间折衷的可对加性分位数回归模型进行估计和变量选择的模型.融合Lasso罚使模型能快速计算,并在局部进行自适应,从而实现对所需分位数甚至极端分位数的预测.同时结合l_(2)罚,在高维数据中将对响应影响较小的协变量函数值压缩为零,实现变量的选择.此外,文中给出保证收敛到全局最优的块坐标ADMM算法(Block Coordinate Alternating Direction Method of Multipliers,BC-ADMM),证明AQFL的预测一致性.在合成数据和碎猪肉数据上的实验表明AQFL在预测准确性和鲁棒性等方面较优.展开更多
Cover crops have long been proposed as an alternative soil management for minimizing erosion rates in olive stands while providing additional ecosystem services.However,the trade-off between these benefits and the com...Cover crops have long been proposed as an alternative soil management for minimizing erosion rates in olive stands while providing additional ecosystem services.However,the trade-off between these benefits and the competition for water with the trees makes the definition of optimal management practices a challenging task in semiarid climates.This work presents an improved version of OliveCan,a process-based simulation model of olive orchards that now can simulate the main impacts of cover crops on the water and carbon balances of olive orchards.Albeit simple in its formulation,the new model components were developed to deal with different cover crop management strategies.Examples are presented for simulation runs of a traditional olive orchard in the conditions of southern Spain,evaluating the effects of different widths for the strip occupied by the cover crop(Fcc)and two contrasting mowing dates.Results revealed that high Fccresulted in lower olive yields,but only when mowing was applied at the end of spring.In this regard,late mowing and high Fccwas associated with lower soil water content from spring to summer,coinciding with olive flowering and the earlier stages of fruit growth.Fccwas also negatively correlated with surface runoff irrespective of the mowing date.On the other hand,net ecosystem productivity(NEP)was substantially affected by both Fccand mowing date.Further simulations under future climate scenarios comparing the same management alternatives are also presented,showing substantial yield reductions by the end of the century and minor or negligible changes in NEP and seasonal runoff.展开更多
In this paper,we apply the method given in the paper“Zero relaxation time limits to a hydrodynamic model of two carrier types for semiconductors”(Mathematische Annalen,2022,382:1031–1046)to study the Cauchy problem...In this paper,we apply the method given in the paper“Zero relaxation time limits to a hydrodynamic model of two carrier types for semiconductors”(Mathematische Annalen,2022,382:1031–1046)to study the Cauchy problem for a one dimensional inhomogeneous hydrodynamic model of two-carrier types for semiconductors with the velocity relaxation.展开更多
In this article,we introduce a nonlinear Caputo-type snakebite envenoming model with memory.The well-known Caputo fractional derivative is used to generalize the previously presented integer-order model into a fractio...In this article,we introduce a nonlinear Caputo-type snakebite envenoming model with memory.The well-known Caputo fractional derivative is used to generalize the previously presented integer-order model into a fractionalorder sense.The numerical solution of the model is derived from a novel implementation of a finite-difference predictor-corrector(L1-PC)scheme with error estimation and stability analysis.The proof of the existence and positivity of the solution is given by using the fixed point theory.From the necessary simulations,we justify that the first-time implementation of the proposedmethod on an epidemicmodel shows that the scheme is fully suitable and time-efficient for solving epidemic models.This work aims to show the novel application of the given scheme as well as to check how the proposed snakebite envenoming model behaves in the presence of the Caputo fractional derivative,including memory effects.展开更多
Fifty-three larch interspecific hybrid clones（Larix kaempferi × L.gmelini） and their parent clones were used for growth curve analysis of height variations.The growth curves of the 55 clones were ＇S＇-shaped a...Fifty-three larch interspecific hybrid clones（Larix kaempferi × L.gmelini） and their parent clones were used for growth curve analysis of height variations.The growth curves of the 55 clones were ＇S＇-shaped and 36 exhibited similar curves as the male parent.The coefficients of the logistic models were higher than 0.943,indicating that our results were effective in the simulation of the growth curves.ANOVA analysis showed significant differences in height of different clones （P／0.01）.Average date of maximum height growth was Day 173,and average duration of rapid growth lasted for 50 days.Annual average increase in height was 9.7cm d^（-1） and daily average increase was 0.2 cm.The ratio of GR to the total annual increase in height ranged from 51.2 to 68.8%,with the average being 59.8%.There was a positive correlation between k values and plant heights which benefited from the evaluation of early plant height.There was also a positive correlation between GR（growth stage）,GD（plant height） and annual increase in height.These results are informative to the evaluation of the elite clone selection and provide a theoretical basis for breeding and management.展开更多
文摘The growth optimizer(GO)is an innovative and robust metaheuristic optimization algorithm designed to simulate the learning and reflective processes experienced by individuals as they mature within the social environment.However,the original GO algorithm is constrained by two significant limitations:slow convergence and high mem-ory requirements.This restricts its application to large-scale and complex problems.To address these problems,this paper proposes an innovative enhanced growth optimizer(eGO).In contrast to conventional population-based optimization algorithms,the eGO algorithm utilizes a probabilistic model,designated as the virtual population,which is capable of accurately replicating the behavior of actual populations while simultaneously reducing memory consumption.Furthermore,this paper introduces the Lévy flight mechanism,which enhances the diversity and flexibility of the search process,thus further improving the algorithm’s global search capability and convergence speed.To verify the effectiveness of the eGO algorithm,a series of experiments were conducted using the CEC2014 and CEC2017 test sets.The results demonstrate that the eGO algorithm outperforms the original GO algorithm and other compact algorithms regarding memory usage and convergence speed,thus exhibiting powerful optimization capabilities.Finally,the eGO algorithm was applied to image fusion.Through a comparative analysis with the existing PSO and GO algorithms and other compact algorithms,the eGO algorithm demonstrates superior performance in image fusion.
文摘In view of the composition analysis and identification of ancient glass products, L1 regularization, K-Means cluster analysis, elbow rule and other methods were comprehensively used to build logical regression, cluster analysis, hyper-parameter test and other models, and SPSS, Python and other tools were used to obtain the classification rules of glass products under different fluxes, sub classification under different chemical compositions, hyper-parameter K value test and rationality analysis. Research can provide theoretical support for the protection and restoration of ancient glass relics.
文摘加性分位数回归为非线性关系的建模提供一种灵活、鲁棒的方法.拟合加性分位数模型的方法通常使用样条函数逼近分量,但需要先验的选择节点,计算速度较慢,并不适合大规模数据问题.因此文中提出基于融合Lasso的非参数加性分位数回归模型(Nonparametric Additive Quantile Regression Model Based on Fused Lasso,AQFL),是在融合Lasso罚和l_(2)罚之间折衷的可对加性分位数回归模型进行估计和变量选择的模型.融合Lasso罚使模型能快速计算,并在局部进行自适应,从而实现对所需分位数甚至极端分位数的预测.同时结合l_(2)罚,在高维数据中将对响应影响较小的协变量函数值压缩为零,实现变量的选择.此外,文中给出保证收敛到全局最优的块坐标ADMM算法(Block Coordinate Alternating Direction Method of Multipliers,BC-ADMM),证明AQFL的预测一致性.在合成数据和碎猪肉数据上的实验表明AQFL在预测准确性和鲁棒性等方面较优.
基金Consejería de Transformación Económica,Industria,Conocimiento y Universidades"("Junta de Andalucía",Spain)through a project cofunded by ERDF[grant number 27425]part of the work was conducted under two projects funded by"Ministerio de Ciencia,Innovación y Universidades"+7 种基金Spain[grant numbers PID2019-110575RB-I00 and PCI2019-103621]one of which into the framework of the MAPPY project(JPIClimate ERA-NET,AXIS call)financial support from"Ministerio de CienciaInnovación y Universidades",through the Severo Ochoa and María de Maeztu Program for Centers and Units of Excellence in R&D[grant number CEX2019-000968-M]granted to the first and second authors by Consejería de Transformación Económica,IndustriaConocimiento y Universidades"("Junta de Andalucia",Spain)[grant number POSTDOC-21-00381]"Ministerio de Universidades(’María Zambrano’scholarship)[grant number 2021/86493],respectively。
文摘Cover crops have long been proposed as an alternative soil management for minimizing erosion rates in olive stands while providing additional ecosystem services.However,the trade-off between these benefits and the competition for water with the trees makes the definition of optimal management practices a challenging task in semiarid climates.This work presents an improved version of OliveCan,a process-based simulation model of olive orchards that now can simulate the main impacts of cover crops on the water and carbon balances of olive orchards.Albeit simple in its formulation,the new model components were developed to deal with different cover crop management strategies.Examples are presented for simulation runs of a traditional olive orchard in the conditions of southern Spain,evaluating the effects of different widths for the strip occupied by the cover crop(Fcc)and two contrasting mowing dates.Results revealed that high Fccresulted in lower olive yields,but only when mowing was applied at the end of spring.In this regard,late mowing and high Fccwas associated with lower soil water content from spring to summer,coinciding with olive flowering and the earlier stages of fruit growth.Fccwas also negatively correlated with surface runoff irrespective of the mowing date.On the other hand,net ecosystem productivity(NEP)was substantially affected by both Fccand mowing date.Further simulations under future climate scenarios comparing the same management alternatives are also presented,showing substantial yield reductions by the end of the century and minor or negligible changes in NEP and seasonal runoff.
基金supported by Zhejiang Province NSFC(LY20A010023 and LY22A010015)the NSFC(12071106)of China+1 种基金supported by the Natural Science Foundation of Jiangsu Province(BK20211293)the“Qing-Lan Engineering”Foundation of Jiangsu Higher Education Institutions。
文摘In this paper,we apply the method given in the paper“Zero relaxation time limits to a hydrodynamic model of two carrier types for semiconductors”(Mathematische Annalen,2022,382:1031–1046)to study the Cauchy problem for a one dimensional inhomogeneous hydrodynamic model of two-carrier types for semiconductors with the velocity relaxation.
文摘In this article,we introduce a nonlinear Caputo-type snakebite envenoming model with memory.The well-known Caputo fractional derivative is used to generalize the previously presented integer-order model into a fractionalorder sense.The numerical solution of the model is derived from a novel implementation of a finite-difference predictor-corrector(L1-PC)scheme with error estimation and stability analysis.The proof of the existence and positivity of the solution is given by using the fixed point theory.From the necessary simulations,we justify that the first-time implementation of the proposedmethod on an epidemicmodel shows that the scheme is fully suitable and time-efficient for solving epidemic models.This work aims to show the novel application of the given scheme as well as to check how the proposed snakebite envenoming model behaves in the presence of the Caputo fractional derivative,including memory effects.
基金supported by Grants from the National Science and Technology Pillar Program of China(No.2015DAD09B01)
文摘Fifty-three larch interspecific hybrid clones（Larix kaempferi × L.gmelini） and their parent clones were used for growth curve analysis of height variations.The growth curves of the 55 clones were ＇S＇-shaped and 36 exhibited similar curves as the male parent.The coefficients of the logistic models were higher than 0.943,indicating that our results were effective in the simulation of the growth curves.ANOVA analysis showed significant differences in height of different clones （P／0.01）.Average date of maximum height growth was Day 173,and average duration of rapid growth lasted for 50 days.Annual average increase in height was 9.7cm d^（-1） and daily average increase was 0.2 cm.The ratio of GR to the total annual increase in height ranged from 51.2 to 68.8%,with the average being 59.8%.There was a positive correlation between k values and plant heights which benefited from the evaluation of early plant height.There was also a positive correlation between GR（growth stage）,GD（plant height） and annual increase in height.These results are informative to the evaluation of the elite clone selection and provide a theoretical basis for breeding and management.
