The high-quality development of the construction industry fundamentally stems from the significant improvement of total factor productivity.Therefore,it is of crucial significance for promoting the development of the ...The high-quality development of the construction industry fundamentally stems from the significant improvement of total factor productivity.Therefore,it is of crucial significance for promoting the development of the construction industry to a higher level by scientifically and accurately measuring the total factor productivity of the construction industry and deeply analyzing the influencing factors behind it.Based on a comprehensive consideration of research methods and influencing factors,this paper systematically reviews the existing relevant literature on total factor productivity in the construction industry,aiming to reveal the current research development trend in this field and point out potential problems.This effort aims to provide a solid theoretical foundation and valuable reference for further in-depth research,and jointly promote the continuous progress and development of total factor productivity research in the construction industry.展开更多
In 2017,American College of Cardiology(ACC)/American Heart Association(AHA)et al.jointly released the latest guidelines for adult hypertension,exactly including prevention,diagnosis,assess and treatment,in which blood...In 2017,American College of Cardiology(ACC)/American Heart Association(AHA)et al.jointly released the latest guidelines for adult hypertension,exactly including prevention,diagnosis,assess and treatment,in which blood pressure levels greater than 130/80 mm Hg were defined as hypertension[1].Based on these modified guidelines,the morbidity of hypertension in US increased from 32%to 46%.展开更多
The geological characteristics and production practices of the major middle-and high-maturity shale oil exploration areas in China are analyzed.Combined with laboratory results,it is clear that three essential conditi...The geological characteristics and production practices of the major middle-and high-maturity shale oil exploration areas in China are analyzed.Combined with laboratory results,it is clear that three essential conditions,i.e.economic initial production,commercial cumulative oil production of single well,and large-scale recoverable reserves confirmed by the testing production,determine whether the continental shale oil can be put into large-scale commercial development.The quantity and quality of movable hydrocarbons are confirmed to be crucial to economic development of shale oil,and focuses in evaluation of shale oil enrichment area/interval.The evaluation indexes of movable hydrocarbon enrichment include:(1)the material basis for forming retained hydrocarbon,including TOC>2%(preferentially 3%-4%),and typeⅠ-Ⅱkerogens;(2)the mobility of retained hydrocarbon,which is closely related to the hydrocarbon composition and flow behaviors of light/heavy components,and can be evaluated from the perspectives of thermal maturity(Ro),gas-oil ratio(GOR),crude oil density,quality of hydrocarbon components,preservation conditions;and(3)the reservoir characteristics associated with the engineering reconstruction,including the main pore throat distribution zone,reservoir physical properties(including fractures),lamellation feature and diagenetic stage,etc.Accordingly,13 evaluation indexes in three categories and their reference values are established.The evaluation indicates that the light shale oil zones in the Gulong Sag of Songliao Basin have the most favorable enrichment conditions of movable hydrocarbons,followed by light oil and black oil zones,containing 20.8×10^(8) t light oil resources in reservoirs with R_(0)>1.2%,pressure coefficient greater than 1.4,effective porosity greater than 6%,crude oil density less than 0.82 g/cm^(3),and GOR>100 m/m^(3).The shale oil in the Gulong Sag can be explored and developed separately by the categories(resource sweet spot,engineering sweet spot,and tight oil sweet spot)depending on shale oil flowability.The Gulong Sag is the most promising area to achieve large-scale breakthrough and production of continental shale oil in China.展开更多
A quantitative research on the effect of coal mining on the soil organic carbon(SOC)pool at regional scale is beneficial to the scientific management of SOC pools in coal mining areas and the realization of coal low-c...A quantitative research on the effect of coal mining on the soil organic carbon(SOC)pool at regional scale is beneficial to the scientific management of SOC pools in coal mining areas and the realization of coal low-carbon mining.Moreover,the spatial prediction model of SOC content suitable for coal mining subsidence area is a scientific problem that must be solved.Tak-ing the Changhe River Basin of Jincheng City,Shanxi Province,China,as the study area,this paper proposed a radial basis function neural network model combined with the ordinary kriging method.The model includes topography and vegetation factors,which have large influence on soil properties in mining areas,as input parameters to predict the spatial distribution of SOC in the 0-20 and 2040 cm soil layers of the study area.And comparing the prediction effect with the direct kriging method,the results show that the mean error,the mean absolute error and the root mean square error between the predicted and measured values of SOC content predicted by the radial basis function neural network are lower than those obtained by the direct kriging method.Based on the fitting effect of the predicted and measured values,the R^(2) obtained by the radial basis artificial neural network are 0.81,0.70,respectively,higher than the value of 0.44 and 0.36 obtained by the direct kriging method.Therefore,the model combining the artificial neural network and kriging,and considering environmental factors can improve the prediction accuracy of the SOC content in mining areas.展开更多
This paper studies the problem applying Radial Basis Function Network(RBFN) which is trained by the Recursive Least Square Algorithm(RLSA) to the recognition of one dimensional images of radar targets. The equivalence...This paper studies the problem applying Radial Basis Function Network(RBFN) which is trained by the Recursive Least Square Algorithm(RLSA) to the recognition of one dimensional images of radar targets. The equivalence between the RBFN and the estimate of Parzen window probabilistic density is proved. It is pointed out that the I/O functions in RBFN hidden units can be generalized to general Parzen window probabilistic kernel function or potential function, too. This paper discusses the effects of the shape parameter a in the RBFN and the forgotten factor A in RLSA on the results of the recognition of three kinds of kernel function such as Gaussian, triangle, double-exponential, at the same time, also discusses the relationship between A and the training time in the RBFN.展开更多
Support vector regression(SVR) method is a novel type of learning machine algorithms,which is seldom applied to the development of urban atmospheric quality models under multiple socio-economic factors.This study pres...Support vector regression(SVR) method is a novel type of learning machine algorithms,which is seldom applied to the development of urban atmospheric quality models under multiple socio-economic factors.This study presents four SVR models by selecting linear,radial basis,spline,and polynomial functions as kernels,respectively for the prediction of urban dust fall levels.The inputs of the models are identified as industrial coal consumption,population density,traffic flow coefficient,and shopping density coefficient.The training and testing results show that the SVR model with radial basis kernel performs better than the other three both in the training and testing processes.In addition,a number of scenario analyses reveal that the most suitable parameters(insensitive loss function ε,the parameter to reduce the influence of error C,and discrete level or average distribution of parameters σ) are 0.001,0.5,and 2000,respectively.展开更多
基金Supported by School-level Natural Science Project of Jiangxi University of Technology(232ZRYB02).
文摘The high-quality development of the construction industry fundamentally stems from the significant improvement of total factor productivity.Therefore,it is of crucial significance for promoting the development of the construction industry to a higher level by scientifically and accurately measuring the total factor productivity of the construction industry and deeply analyzing the influencing factors behind it.Based on a comprehensive consideration of research methods and influencing factors,this paper systematically reviews the existing relevant literature on total factor productivity in the construction industry,aiming to reveal the current research development trend in this field and point out potential problems.This effort aims to provide a solid theoretical foundation and valuable reference for further in-depth research,and jointly promote the continuous progress and development of total factor productivity research in the construction industry.
基金supported by the National Natural Science Foundation of China[81670706&81800736]Natural Science Foundation of Shandong Province[ZR2019PH078].
文摘In 2017,American College of Cardiology(ACC)/American Heart Association(AHA)et al.jointly released the latest guidelines for adult hypertension,exactly including prevention,diagnosis,assess and treatment,in which blood pressure levels greater than 130/80 mm Hg were defined as hypertension[1].Based on these modified guidelines,the morbidity of hypertension in US increased from 32%to 46%.
基金Supported by the National Natural Science Foundation of China(U22B6004)the PetroChina Research Institute of Petroleum Exploration&Development Project(2022yjcq03).
文摘The geological characteristics and production practices of the major middle-and high-maturity shale oil exploration areas in China are analyzed.Combined with laboratory results,it is clear that three essential conditions,i.e.economic initial production,commercial cumulative oil production of single well,and large-scale recoverable reserves confirmed by the testing production,determine whether the continental shale oil can be put into large-scale commercial development.The quantity and quality of movable hydrocarbons are confirmed to be crucial to economic development of shale oil,and focuses in evaluation of shale oil enrichment area/interval.The evaluation indexes of movable hydrocarbon enrichment include:(1)the material basis for forming retained hydrocarbon,including TOC>2%(preferentially 3%-4%),and typeⅠ-Ⅱkerogens;(2)the mobility of retained hydrocarbon,which is closely related to the hydrocarbon composition and flow behaviors of light/heavy components,and can be evaluated from the perspectives of thermal maturity(Ro),gas-oil ratio(GOR),crude oil density,quality of hydrocarbon components,preservation conditions;and(3)the reservoir characteristics associated with the engineering reconstruction,including the main pore throat distribution zone,reservoir physical properties(including fractures),lamellation feature and diagenetic stage,etc.Accordingly,13 evaluation indexes in three categories and their reference values are established.The evaluation indicates that the light shale oil zones in the Gulong Sag of Songliao Basin have the most favorable enrichment conditions of movable hydrocarbons,followed by light oil and black oil zones,containing 20.8×10^(8) t light oil resources in reservoirs with R_(0)>1.2%,pressure coefficient greater than 1.4,effective porosity greater than 6%,crude oil density less than 0.82 g/cm^(3),and GOR>100 m/m^(3).The shale oil in the Gulong Sag can be explored and developed separately by the categories(resource sweet spot,engineering sweet spot,and tight oil sweet spot)depending on shale oil flowability.The Gulong Sag is the most promising area to achieve large-scale breakthrough and production of continental shale oil in China.
基金supported by the National Natural Science Foundation of China (51304130)the Natural Science Foundation of Shanxi Province,China (2015021125)+4 种基金Shanxi Provincial People's Government Major Decision Consulting Project (ZB20211703)Program for the Soft Science research of Shanxi (2018041060-2)Program for the Philosophy and Social Sciences Research of Higher Learning Institutions of Shanxi (201803010)Philosophy and Social Sciences Planning Project of Shanxi Province (2020YJ052)Basic Research Program of Shanxi Province (20210302123403).
文摘A quantitative research on the effect of coal mining on the soil organic carbon(SOC)pool at regional scale is beneficial to the scientific management of SOC pools in coal mining areas and the realization of coal low-carbon mining.Moreover,the spatial prediction model of SOC content suitable for coal mining subsidence area is a scientific problem that must be solved.Tak-ing the Changhe River Basin of Jincheng City,Shanxi Province,China,as the study area,this paper proposed a radial basis function neural network model combined with the ordinary kriging method.The model includes topography and vegetation factors,which have large influence on soil properties in mining areas,as input parameters to predict the spatial distribution of SOC in the 0-20 and 2040 cm soil layers of the study area.And comparing the prediction effect with the direct kriging method,the results show that the mean error,the mean absolute error and the root mean square error between the predicted and measured values of SOC content predicted by the radial basis function neural network are lower than those obtained by the direct kriging method.Based on the fitting effect of the predicted and measured values,the R^(2) obtained by the radial basis artificial neural network are 0.81,0.70,respectively,higher than the value of 0.44 and 0.36 obtained by the direct kriging method.Therefore,the model combining the artificial neural network and kriging,and considering environmental factors can improve the prediction accuracy of the SOC content in mining areas.
基金Supported by the National Natural Science Foundationthe Doctoral Foundation of the State Education Commission of China
文摘This paper studies the problem applying Radial Basis Function Network(RBFN) which is trained by the Recursive Least Square Algorithm(RLSA) to the recognition of one dimensional images of radar targets. The equivalence between the RBFN and the estimate of Parzen window probabilistic density is proved. It is pointed out that the I/O functions in RBFN hidden units can be generalized to general Parzen window probabilistic kernel function or potential function, too. This paper discusses the effects of the shape parameter a in the RBFN and the forgotten factor A in RLSA on the results of the recognition of three kinds of kernel function such as Gaussian, triangle, double-exponential, at the same time, also discusses the relationship between A and the training time in the RBFN.
基金Projects(2007JT3018, 2008JT1013, 2009FJ4056) supported by the Key Project in Hunan Science and Technology Program, ChinaProject(20090161120014) supported by the New Teachers Sustentation Fund in Doctoral Program, Ministry of Education, China
文摘Support vector regression(SVR) method is a novel type of learning machine algorithms,which is seldom applied to the development of urban atmospheric quality models under multiple socio-economic factors.This study presents four SVR models by selecting linear,radial basis,spline,and polynomial functions as kernels,respectively for the prediction of urban dust fall levels.The inputs of the models are identified as industrial coal consumption,population density,traffic flow coefficient,and shopping density coefficient.The training and testing results show that the SVR model with radial basis kernel performs better than the other three both in the training and testing processes.In addition,a number of scenario analyses reveal that the most suitable parameters(insensitive loss function ε,the parameter to reduce the influence of error C,and discrete level or average distribution of parameters σ) are 0.001,0.5,and 2000,respectively.
