The resilient modulus(MR)of subgrade soils is usually used to characterize the stiffness of subgrade and is a crucial parameter in pavement design.In order to determine the resilient modulus of compacted subgrade soil...The resilient modulus(MR)of subgrade soils is usually used to characterize the stiffness of subgrade and is a crucial parameter in pavement design.In order to determine the resilient modulus of compacted subgrade soils quickly and accurately,an optimized artificial neural network(ANN)approach based on the multi-population genetic algorithm(MPGA)was proposed in this study.The MPGA overcomes the problems of the traditional ANN such as low efficiency,local optimum and over-fitting.The developed optimized ANN method consists of ten input variables,twenty-one hidden neurons,and one output variable.The physical properties(liquid limit,plastic limit,plasticity index,0.075 mm passing percentage,maximum dry density,optimum moisture content),state variables(degree of compaction,moisture content)and stress variables(confining pressure,deviatoric stress)of subgrade soils were selected as input variables.The MR was directly used as the output variable.Then,adopting a large amount of experimental data from existing literature,the developed optimized ANN method was compared with the existing representative estimation methods.The results show that the developed optimized ANN method has the advantages of fast speed,strong generalization ability and good accuracy in MR estimation.展开更多
Structural biology has been paying more attention on biomolecular complexes over the past decades,since they are crucial for many biological processes.Among these techniques for structural determination,nuclear magnet...Structural biology has been paying more attention on biomolecular complexes over the past decades,since they are crucial for many biological processes.Among these techniques for structural determination,nuclear magnetic resonance(NMR)has its advantage when dealing with biomolecules with high flexibility in solution.Small-angle X-ray scattering(SAXS)is a very important complementary technique that provides information on global shape of biomolecules.For biomolecular complexes,it can be much easier to determine atomic structures of individual subunits through NMR.In addition,NMR can also provide other structural information,such as the interface and orientations between subunits,and long range distance and angular restraints.Therefore,to construct structural models of biomolecular complexes,it would be very appropriate to combine experimental restraints obtained through NMR and low-resolution shape information from SAXS by utilizing computational tools,which is the main topic of this review.展开更多
基金Project(51878078)supported by the National Natural Science Foundation of ChinaProject(2018-025)supported by the Training Program for High-level Technical Personnel in Transportation Industry,ChinaProject(CTKY-PTRC-2018-003)supported by the Design Theory,Method and Demonstration of Durability Asphalt Pavement Based on Heavy-duty Traffic Conditions in Shanghai Area,China。
文摘The resilient modulus(MR)of subgrade soils is usually used to characterize the stiffness of subgrade and is a crucial parameter in pavement design.In order to determine the resilient modulus of compacted subgrade soils quickly and accurately,an optimized artificial neural network(ANN)approach based on the multi-population genetic algorithm(MPGA)was proposed in this study.The MPGA overcomes the problems of the traditional ANN such as low efficiency,local optimum and over-fitting.The developed optimized ANN method consists of ten input variables,twenty-one hidden neurons,and one output variable.The physical properties(liquid limit,plastic limit,plasticity index,0.075 mm passing percentage,maximum dry density,optimum moisture content),state variables(degree of compaction,moisture content)and stress variables(confining pressure,deviatoric stress)of subgrade soils were selected as input variables.The MR was directly used as the output variable.Then,adopting a large amount of experimental data from existing literature,the developed optimized ANN method was compared with the existing representative estimation methods.The results show that the developed optimized ANN method has the advantages of fast speed,strong generalization ability and good accuracy in MR estimation.
基金The National Key Basic Research Program of China(2013CB910203)the National Natural Science Foundation of China(31270760)+1 种基金the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB08030102)the Specialized Research Fund for the Doctoral Program of Higher Education(20113402120013)
文摘Structural biology has been paying more attention on biomolecular complexes over the past decades,since they are crucial for many biological processes.Among these techniques for structural determination,nuclear magnetic resonance(NMR)has its advantage when dealing with biomolecules with high flexibility in solution.Small-angle X-ray scattering(SAXS)is a very important complementary technique that provides information on global shape of biomolecules.For biomolecular complexes,it can be much easier to determine atomic structures of individual subunits through NMR.In addition,NMR can also provide other structural information,such as the interface and orientations between subunits,and long range distance and angular restraints.Therefore,to construct structural models of biomolecular complexes,it would be very appropriate to combine experimental restraints obtained through NMR and low-resolution shape information from SAXS by utilizing computational tools,which is the main topic of this review.
