This paper makes a comprehensive analysis on the characteristics and influencing factors of regional allocation of new construction land use indicators,and determines the primary indicators from social,economic,extern...This paper makes a comprehensive analysis on the characteristics and influencing factors of regional allocation of new construction land use indicators,and determines the primary indicators from social,economic,external and internal factors.Using Delphi method and correlation analysis,this paper selects indicators and establishes evaluation indicator system.Using entropy method and AHP,this paper determines the weight of indicators,rationally allocates new construction land,and uses the actual data in Huai'an City for case studies,so as to provide a reference for land use planning.In addition,this paper makes a comparative analysis on the land use internal factors as important factors,in order to make the weight assigning more in line with the actual situation of construction land in Huai'an.展开更多
The remaining useful life prediction of rolling bearing is vital in safety and reliability guarantee.In engineering scenarios,only a small amount of bearing performance degradation data can be obtained through acceler...The remaining useful life prediction of rolling bearing is vital in safety and reliability guarantee.In engineering scenarios,only a small amount of bearing performance degradation data can be obtained through accelerated life testing.In the absence of lifetime data,the hidden long-term correlation between performance degradation data is challenging to mine effectively,which is the main factor that restricts the prediction precision and engineering application of the residual life prediction method.To address this problem,a novel method based on the multi-layer perception neural network and bidirectional long short-term memory network is proposed.Firstly,a nonlinear health indicator(HI)calculation method based on kernel principal component analysis(KPCA)and exponential weighted moving average(EWMA)is designed.Then,using the raw vibration data and HI,a multi-layer perceptron(MLP)neural network is trained to further calculate the HI of the online bearing in real time.Furthermore,The bidirectional long short-term memory model(BiLSTM)optimized by particle swarm optimization(PSO)is used to mine the time series features of HI and predict the remaining service life.Performance verification experiments and comparative experiments are carried out on the XJTU-SY bearing open dataset.The research results indicate that this method has an excellent ability to predict future HI and remaining life.展开更多
Construction Industry operates relying on various key economic indicators.One of these indicators is material prices.On the other hand,cost is a key concern in all operations of the construction industry.In the uncert...Construction Industry operates relying on various key economic indicators.One of these indicators is material prices.On the other hand,cost is a key concern in all operations of the construction industry.In the uncertain conditions,reliable cost forecasts become an important source of information.Material cost is one of the key components of the overall cost of construction.In addition,cost overrun is a common problem in the construction industry,where nine out of ten construction projects face cost overrun.In order to carry out a successful cost management strategy and prevent cost overruns,it is very important to find reliable methods for the estimation of construction material prices.Material prices have a time dependent nature.In order to increase the foreseeability of the costs of construction materials,this study focuses on estimation of construction material indices through time series analysis.Two different types of analysis are implemented for estimation of the future values of construction material indices.The first method implemented was Autoregressive Integrated Moving Average(ARIMA),which is known to be successful in estimation of time series having a linear nature.The second method implementedwas Non-LinearAutoregressive Neural Network(NARNET)which is known to be successful in modeling and estimating of series with non-linear components.The results have shown that depending on the nature of the series,both these methods can successfully and accurately estimate the future values of the indices.In addition,we found out that Optimal NARNET architectures which provide better accuracy in estimation of the series can be identified/discovered as result of grid search on NARNET hyperparameters.展开更多
The MBTI(Myers-Briggs Type Indicator)remains widely used in many counseling applications despite extensive criticism of its basic nature and psychometric properties.The present study was designed to examine specifical...The MBTI(Myers-Briggs Type Indicator)remains widely used in many counseling applications despite extensive criticism of its basic nature and psychometric properties.The present study was designed to examine specifically the accuracy of the claimed minimal influence of social desirability on Form G of the MBTI.Undergraduate students(n=26)judged the desirability of each item option of Form G,which was compared across the 60 item pairs in which both options were scored.The rated values were approximately equal for two domains,while J and E item options were judged to be more desirable than their P and I paired response options.A second study(n=52)evaluated the social desirability of the 16 MBTI type descriptors,finding most descriptions to be above the neutral range in desirability.These results suggest that stylistic responding contaminates MBTI profiles and interpretative material.Consequently,users should consider alternative measures and at the very least,take great care in interpreting the MBTI because of its flawed structure.展开更多
文摘This paper makes a comprehensive analysis on the characteristics and influencing factors of regional allocation of new construction land use indicators,and determines the primary indicators from social,economic,external and internal factors.Using Delphi method and correlation analysis,this paper selects indicators and establishes evaluation indicator system.Using entropy method and AHP,this paper determines the weight of indicators,rationally allocates new construction land,and uses the actual data in Huai'an City for case studies,so as to provide a reference for land use planning.In addition,this paper makes a comparative analysis on the land use internal factors as important factors,in order to make the weight assigning more in line with the actual situation of construction land in Huai'an.
基金supported by the National Key Research and Development Project(Grant Number 2023YFB3709601)the National Natural Science Foundation of China(Grant Numbers 62373215,62373219,62073193)+2 种基金the Key Research and Development Plan of Shandong Province(Grant Numbers 2021CXGC010204,2022CXGC020902)the Fundamental Research Funds of Shandong University(Grant Number 2021JCG008)the Natural Science Foundation of Shandong Province(Grant Number ZR2023MF100).
文摘The remaining useful life prediction of rolling bearing is vital in safety and reliability guarantee.In engineering scenarios,only a small amount of bearing performance degradation data can be obtained through accelerated life testing.In the absence of lifetime data,the hidden long-term correlation between performance degradation data is challenging to mine effectively,which is the main factor that restricts the prediction precision and engineering application of the residual life prediction method.To address this problem,a novel method based on the multi-layer perception neural network and bidirectional long short-term memory network is proposed.Firstly,a nonlinear health indicator(HI)calculation method based on kernel principal component analysis(KPCA)and exponential weighted moving average(EWMA)is designed.Then,using the raw vibration data and HI,a multi-layer perceptron(MLP)neural network is trained to further calculate the HI of the online bearing in real time.Furthermore,The bidirectional long short-term memory model(BiLSTM)optimized by particle swarm optimization(PSO)is used to mine the time series features of HI and predict the remaining service life.Performance verification experiments and comparative experiments are carried out on the XJTU-SY bearing open dataset.The research results indicate that this method has an excellent ability to predict future HI and remaining life.
基金supported by the Energy Cloud R&D Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Science,ICT(2019M3F2A1073164)MSGSU BAP(2021-25).
文摘Construction Industry operates relying on various key economic indicators.One of these indicators is material prices.On the other hand,cost is a key concern in all operations of the construction industry.In the uncertain conditions,reliable cost forecasts become an important source of information.Material cost is one of the key components of the overall cost of construction.In addition,cost overrun is a common problem in the construction industry,where nine out of ten construction projects face cost overrun.In order to carry out a successful cost management strategy and prevent cost overruns,it is very important to find reliable methods for the estimation of construction material prices.Material prices have a time dependent nature.In order to increase the foreseeability of the costs of construction materials,this study focuses on estimation of construction material indices through time series analysis.Two different types of analysis are implemented for estimation of the future values of construction material indices.The first method implemented was Autoregressive Integrated Moving Average(ARIMA),which is known to be successful in estimation of time series having a linear nature.The second method implementedwas Non-LinearAutoregressive Neural Network(NARNET)which is known to be successful in modeling and estimating of series with non-linear components.The results have shown that depending on the nature of the series,both these methods can successfully and accurately estimate the future values of the indices.In addition,we found out that Optimal NARNET architectures which provide better accuracy in estimation of the series can be identified/discovered as result of grid search on NARNET hyperparameters.
文摘The MBTI(Myers-Briggs Type Indicator)remains widely used in many counseling applications despite extensive criticism of its basic nature and psychometric properties.The present study was designed to examine specifically the accuracy of the claimed minimal influence of social desirability on Form G of the MBTI.Undergraduate students(n=26)judged the desirability of each item option of Form G,which was compared across the 60 item pairs in which both options were scored.The rated values were approximately equal for two domains,while J and E item options were judged to be more desirable than their P and I paired response options.A second study(n=52)evaluated the social desirability of the 16 MBTI type descriptors,finding most descriptions to be above the neutral range in desirability.These results suggest that stylistic responding contaminates MBTI profiles and interpretative material.Consequently,users should consider alternative measures and at the very least,take great care in interpreting the MBTI because of its flawed structure.
