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Anisotropic time-dependent behaviors of shale under direct shearing and associated empirical creep models 被引量:2
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作者 Yachen Xie Michael Z.Hou +1 位作者 Hejuan Liu Cunbao Li 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2024年第4期1262-1279,共18页
Understanding the anisotropic creep behaviors of shale under direct shearing is a challenging issue.In this context,we conducted shear-creep and steady-creep tests on shale with five bedding orientations (i.e.0°,... Understanding the anisotropic creep behaviors of shale under direct shearing is a challenging issue.In this context,we conducted shear-creep and steady-creep tests on shale with five bedding orientations (i.e.0°,30°,45°,60°,and 90°),under multiple levels of direct shearing for the first time.The results show that the anisotropic creep of shale exhibits a significant stress-dependent behavior.Under a low shear stress,the creep compliance of shale increases linearly with the logarithm of time at all bedding orientations,and the increase depends on the bedding orientation and creep time.Under high shear stress conditions,the creep compliance of shale is minimal when the bedding orientation is 0°,and the steady-creep rate of shale increases significantly with increasing bedding orientations of 30°,45°,60°,and 90°.The stress-strain values corresponding to the inception of the accelerated creep stage show an increasing and then decreasing trend with the bedding orientation.A semilogarithmic model that could reflect the stress dependence of the steady-creep rate while considering the hardening and damage process is proposed.The model minimizes the deviation of the calculated steady-state creep rate from the observed value and reveals the behavior of the bedding orientation's influence on the steady-creep rate.The applicability of the five classical empirical creep models is quantitatively evaluated.It shows that the logarithmic model can well explain the experimental creep strain and creep rate,and it can accurately predict long-term shear creep deformation.Based on an improved logarithmic model,the variations in creep parameters with shear stress and bedding orientations are discussed.With abovementioned findings,a mathematical method for constructing an anisotropic shear creep model of shale is proposed,which can characterize the nonlinear dependence of the anisotropic shear creep behavior of shale on the bedding orientation. 展开更多
关键词 Rock anisotropy Direct shear creep Creep compliance Steady-creep rate Empirical model Creep constitutive model
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Price prediction of power transformer materials based on CEEMD and GRU
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作者 Yan Huang Yufeng Hu +2 位作者 Liangzheng Wu Shangyong Wen Zhengdong Wan 《Global Energy Interconnection》 EI CSCD 2024年第2期217-227,共11页
The rapid growth of the Chinese economy has fueled the expansion of power grids.Power transformers are key equipment in power grid projects,and their price changes have a significant impact on cost control.However,the... The rapid growth of the Chinese economy has fueled the expansion of power grids.Power transformers are key equipment in power grid projects,and their price changes have a significant impact on cost control.However,the prices of power transformer materials manifest as nonsmooth and nonlinear sequences.Hence,estimating the acquisition costs of power grid projects is difficult,hindering the normal operation of power engineering construction.To more accurately predict the price of power transformer materials,this study proposes a method based on complementary ensemble empirical mode decomposition(CEEMD)and gated recurrent unit(GRU)network.First,the CEEMD decomposed the price series into multiple intrinsic mode functions(IMFs).Multiple IMFs were clustered to obtain several aggregated sequences based on the sample entropy of each IMF.Then,an empirical wavelet transform(EWT)was applied to the aggregation sequence with a large sample entropy,and the multiple subsequences obtained from the decomposition were predicted by the GRU model.The GRU model was used to directly predict the aggregation sequences with a small sample entropy.In this study,we used authentic historical pricing data for power transformer materials to validate the proposed approach.The empirical findings demonstrated the efficacy of our method across both datasets,with mean absolute percentage errors(MAPEs)of less than 1%and 3%.This approach holds a significant reference value for future research in the field of power transformer material price prediction. 展开更多
关键词 Power transformer material Price prediction Complementary ensemble empirical mode decomposition Gated recurrent unit Empirical wavelet transform
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Spatio-temporal variability of surface chlorophyll a in the Yellow Sea and the East China Sea based on reconstructions of satellite data of 2001-2020
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作者 Weichen XIE Tao WANG Wensheng JIANG 《Journal of Oceanology and Limnology》 SCIE CAS CSCD 2024年第2期390-407,共18页
Chlorophyll-a(Chl-a)concentration is a primary indicator for marine environmental monitoring.The spatio-temporal variations of sea surface Chl-a concentration in the Yellow Sea(YS)and the East China Sea(ECS)in 2001-20... Chlorophyll-a(Chl-a)concentration is a primary indicator for marine environmental monitoring.The spatio-temporal variations of sea surface Chl-a concentration in the Yellow Sea(YS)and the East China Sea(ECS)in 2001-2020 were investigated by reconstructing the MODIS Level 3 products with the data interpolation empirical orthogonal function(DINEOF)method.The reconstructed results by interpolating the combined MODIS daily+8-day datasets were found better than those merely by interpolating daily or 8-day data.Chl-a concentration in the YS and the ECS reached its maximum in spring,with blooms occurring,decreased in summer and autumn,and increased in late autumn and early winter.By performing empirical orthogonal function(EOF)decomposition of the reconstructed data fields and correlation analysis with several potential environmental factors,we found that the sea surface temperature(SST)plays a significant role in the seasonal variation of Chl a,especially during spring and summer.The increase of SST in spring and the upper-layer nutrients mixed up during the last winter might favor the occurrence of spring blooms.The high sea surface temperature(SST)throughout the summer would strengthen the vertical stratification and prevent nutrients supply from deep water,resulting in low surface Chl-a concentrations.The sea surface Chl-a concentration in the YS was found decreased significantly from 2012 to 2020,which was possibly related to the Pacific Decadal Oscillation(PDO). 展开更多
关键词 chlorophyll a(Chl a) data interpolation empirical orthogonal function(DINEOF) empirical orthogonal function(EOF)analysis Yellow Sea East China Sea
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Assessment of the three representative empirical models for zenith tropospheric delay(ZTD)using the CMONOC data
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作者 Debao Yuan Jian Li +4 位作者 Yifan Yao Fei Yang Yingying Wang Ran Chen Tairan Xu 《Geodesy and Geodynamics》 EI CSCD 2024年第5期488-494,共7页
The precise correction of atmospheric zenith tropospheric delay(ZTD)is significant for the Global Navigation Satellite System(GNSS)performance regarding positioning accuracy and convergence time.In the past decades,ma... The precise correction of atmospheric zenith tropospheric delay(ZTD)is significant for the Global Navigation Satellite System(GNSS)performance regarding positioning accuracy and convergence time.In the past decades,many empirical ZTD models based on whether the gridded or scattered ZTD products have been proposed and widely used in the GNSS positioning applications.But there is no comprehensive evaluation of these models for the whole China region,which features complicated topography and climate.In this study,we completely assess the typical empirical models,the IGGtropSH model(gridded,non-meteorology),the SHAtropE model(scattered,non-meteorology),and the GPT3 model(gridded,meteorology)using the Crustal Movement Observation Network of China(CMONOC)network.In general,the results show that the three models share consistent performance with RMSE/bias of 37.45/1.63,37.13/2.20,and 38.27/1.34 mm for the GPT3,SHAtropE and IGGtropSH model,respectively.However,the models had a distinct performance regarding geographical distribution,elevation,seasonal variations,and daily variation.In the southeastern region of China,RMSE values are around 50 mm,which are much higher than that in the western region,approximately 20 mm.The SHAtropE model exhibits better performance for areas with large variations in elevation.The GPT3 model and the IGGtropSH model are more stable across different months,and the SHAtropE model based on the GNSS data exhibits superior performance across various UTC epochs. 展开更多
关键词 GNSS Zenith tropospheric delay Empirical ZTD model CMONOC data
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Interatomic Interaction Models for Magnetic Materials:Recent Advances
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作者 Tatiana S.Kostiuchenko Alexander V.Shapeev Ivan S.Novikov 《Chinese Physics Letters》 SCIE EI CAS CSCD 2024年第6期54-66,共13页
Atomistic modeling is a widely employed theoretical method of computational materials science.It has found particular utility in the study of magnetic materials.Initially,magnetic empirical interatomic potentials or s... Atomistic modeling is a widely employed theoretical method of computational materials science.It has found particular utility in the study of magnetic materials.Initially,magnetic empirical interatomic potentials or spinpolarized density functional theory(DFT)served as the primary models for describing interatomic interactions in atomistic simulations of magnetic systems.Furthermore,in recent years,a new class of interatomic potentials known as magnetic machine-learning interatomic potentials(magnetic MLIPs)has emerged.These MLIPs combine the computational efficiency,in terms of CPU time,of empirical potentials with the accuracy of DFT calculations.In this review,our focus lies on providing a comprehensive summary of the interatomic interaction models developed specifically for investigating magnetic materials.We also delve into the various problem classes to which these models can be applied.Finally,we offer insights into the future prospects of interatomic interaction model development for the exploration of magnetic materials. 展开更多
关键词 MATERIALS INTERACTION empirical
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Mechanical response and dilatancy characteristics of deep marble under different stress paths:A sight from energy dissipation
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作者 LIU Xiao-hui HAO Qi-jun +2 位作者 ZHENG Yu ZHANG Zhao-peng XUE Yang 《Journal of Central South University》 SCIE EI CAS CSCD 2024年第6期2070-2086,共17页
Dilatancy is a fundamental volumetric growth behavior observed during loading and serves as a key index to comprehending the intricate nonlinear behavior and constitutive equation structure of rock.This study focuses ... Dilatancy is a fundamental volumetric growth behavior observed during loading and serves as a key index to comprehending the intricate nonlinear behavior and constitutive equation structure of rock.This study focuses on Jinping marble obtained from the Jinping Underground Laboratory in China at a depth of 2400 m.Various uniaxial and triaxial tests at different strain rates,along with constant confining pressure tests and reduced confining pressure tests under different confining pressures were conducted to analyze the mechanical response and dilatancy characteristics of the marble under four stress paths.Subsequently,a new empirical dilatancy coefficient is proposed based on the energy dissipation method.The results show that brittle failure characteristics of marble under uniaxial compression are more obvious with the strain rate increasing,and plastic failure characteristics of marble under triaxial compression are gradually strengthened.Furthermore,compared to the constant confining pressure,the volume expansion is relatively lower under unloading condition.The energy dissipation is closely linked to the process of dilatancy,with a rapid increase of dissipated energy coinciding with the beginning of dilatancy.A new empirical dilatancy coefficient is defined according to the change trend of energy dissipation rate curve,of which change trend is consistent with the actual dilatancy response in marble under different stress paths.The existing empirical and theoretical dilatancy models are analyzed,which shows that the empirical dilatancy coefficient based on the energy background is more universal. 展开更多
关键词 deep marble stress paths DILATANCY energy dissipation empirical dilatancy coefficient
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Empirical likelihood for spatial cross-sectional data models with matrix exponential spatial specification
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作者 LIU Yan RONG Jian-rong QIN Yong-song 《Applied Mathematics(A Journal of Chinese Universities)》 SCIE CSCD 2024年第1期125-139,共15页
In this paper,we study spatial cross-sectional data models in the form of matrix exponential spatial specification(MESS),where MESS appears in both dependent and error terms.The empirical likelihood(EL)ratio statistic... In this paper,we study spatial cross-sectional data models in the form of matrix exponential spatial specification(MESS),where MESS appears in both dependent and error terms.The empirical likelihood(EL)ratio statistics are established for the parameters of the MESS model.It is shown that the limiting distributions of EL ratio statistics follow chi-square distributions,which are used to construct the confidence regions of model parameters.Simulation experiments are conducted to compare the performances of confidence regions based on EL method and normal approximation method. 展开更多
关键词 MESS empirical likelihood con dence region
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Spatial and Temporal Differences of Climate Suitability of Ice and Snow Sports in Major Ski Tourism Destinations in China
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作者 XIE Xia PANG Zhengjin +2 位作者 ZHU Haiqiang GAO Jun ZHOU Qiaoya 《Chinese Geographical Science》 SCIE CSCD 2024年第5期967-982,共16页
Ice and snow tourism in China has grown significantly since the country successfully hosted the Beijing Winter Olympics.Climatic conditions profoundly impact the development of ice and snow tourism;however,most studie... Ice and snow tourism in China has grown significantly since the country successfully hosted the Beijing Winter Olympics.Climatic conditions profoundly impact the development of ice and snow tourism;however,most studies have focused on constructing different climate suitability indicators for ice and snow tourism to evaluate individual regions,lacking horizontal comparative studies across multiple regions.This study aims to enrich the connotation of climate suitability for ice and snow sports,establish an evaluation model based on snowfall amount,temperature,and wind speed,and use daily meteorological data from 1991 to 2021 to horizontally compare the climate suitability for ice and snow sports in major ski tourism destinations in China.This study boasts four major findings:1)the average ice and snow sports climate index of each region decreases over time,and the overall suitability of the climate for ice and snow sports is reducing;2)northern Xinjiang exhibits the most evident regional differentiation from‘very suitable’to‘generally suitable’;3)the spatial zoning of climate suitability for ice and snow sports exhibits heterogeneity,as northern Xinjiang is divided into two‘suitable and above’zones with rotating empirical orthogonal function(REOF).Correspondingly,the four provinces of Hebei,Heilongjiang,Jilin,and Liaoning are divided into three‘generally suitable and above’zones;4)snowfall amount is the main factor affecting the climate suitability of ice and snow sports in the major ski tourist destinations in China. 展开更多
关键词 ice and snow tourism climate suitability rotating empirical orthogonal function(REOF) spatial division China
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Research on the longitudinal protection of a through-type cophase traction direct power supply system based on the empirical wavelet transform
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作者 Lu Li Zeduan Zhang +5 位作者 Wang Cai Qikang Zhuang Guihong Bi Jian Deng Shilong Chen Xiaorui Kan 《Global Energy Interconnection》 EI CSCD 2024年第2期206-216,共11页
This paper proposes a longitudinal protection scheme utilizing empirical wavelet transform(EWT)for a through-type cophase traction direct power supply system,where both sides of a traction network line exhibit a disti... This paper proposes a longitudinal protection scheme utilizing empirical wavelet transform(EWT)for a through-type cophase traction direct power supply system,where both sides of a traction network line exhibit a distinctive boundary structure.This approach capitalizes on the boundary’s capacity to attenuate the high-frequency component of fault signals,resulting in a variation in the high-frequency transient energy ratio when faults occur inside or outside the line.During internal line faults,the high-frequency transient energy at the checkpoints located at both ends surpasses that of its neighboring lines.Conversely,for faults external to the line,the energy is lower compared to adjacent lines.EWT is employed to decompose the collected fault current signals,allowing access to the high-frequency transient energy.The longitudinal protection for the traction network line is established based on disparities between both ends of the traction network line and the high-frequency transient energy on either side of the boundary.Moreover,simulation verification through experimental results demonstrates the effectiveness of the proposed protection scheme across various initial fault angles,distances to faults,and fault transition resistances. 展开更多
关键词 Through-type Cophase traction direct power supply system Traction network Empirical wavelet transform(EWT) Longitudinal protection
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An Enhanced Ensemble-Based Long Short-Term Memory Approach for Traffic Volume Prediction
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作者 Duy Quang Tran Huy Q.Tran Minh Van Nguyen 《Computers, Materials & Continua》 SCIE EI 2024年第3期3585-3602,共18页
With the advancement of artificial intelligence,traffic forecasting is gaining more and more interest in optimizing route planning and enhancing service quality.Traffic volume is an influential parameter for planning ... With the advancement of artificial intelligence,traffic forecasting is gaining more and more interest in optimizing route planning and enhancing service quality.Traffic volume is an influential parameter for planning and operating traffic structures.This study proposed an improved ensemble-based deep learning method to solve traffic volume prediction problems.A set of optimal hyperparameters is also applied for the suggested approach to improve the performance of the learning process.The fusion of these methodologies aims to harness ensemble empirical mode decomposition’s capacity to discern complex traffic patterns and long short-term memory’s proficiency in learning temporal relationships.Firstly,a dataset for automatic vehicle identification is obtained and utilized in the preprocessing stage of the ensemble empirical mode decomposition model.The second aspect involves predicting traffic volume using the long short-term memory algorithm.Next,the study employs a trial-and-error approach to select a set of optimal hyperparameters,including the lookback window,the number of neurons in the hidden layers,and the gradient descent optimization.Finally,the fusion of the obtained results leads to a final traffic volume prediction.The experimental results show that the proposed method outperforms other benchmarks regarding various evaluation measures,including mean absolute error,root mean squared error,mean absolute percentage error,and R-squared.The achieved R-squared value reaches an impressive 98%,while the other evaluation indices surpass the competing.These findings highlight the accuracy of traffic pattern prediction.Consequently,this offers promising prospects for enhancing transportation management systems and urban infrastructure planning. 展开更多
关键词 Ensemble empirical mode decomposition traffic volume prediction long short-term memory optimal hyperparameters deep learning
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Spatiotemporal variations of parameters of internal solitary waves in the northern South China Sea
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作者 Yu’ang LIU Yifei JIANG +3 位作者 Xiaojiang ZHANG Zhiyuan WANG Yu CAO Huizan WANG 《Journal of Oceanology and Limnology》 SCIE CAS CSCD 2024年第2期421-438,共18页
The dynamic parameters for internal solitary waves(ISWs)derived from the extended Korteweg-de Vries(eKdV)equation play an important role in the understanding and prediction of ISWs.The spatiotemporal variations of the... The dynamic parameters for internal solitary waves(ISWs)derived from the extended Korteweg-de Vries(eKdV)equation play an important role in the understanding and prediction of ISWs.The spatiotemporal variations of the dynamic parameters of the ISWs in the northern South China Sea(SCS)were studied based on the reanalysis of long-term temperature and salinity datasets.The results for spectrum analysis show that there are definite geographical differences for the periodic variation of the parameters:in shallow water,all parameters vary with a wave period of one year,while in deep water wave components of the parameters at other frequencies exist.Using wavelet analysis,the wavelet power spectral densities in deep water exhibited an inter-annual variation pattern.For example,the wave component of the dispersion coefficient with a wave period of about half a year reached its power peak once every two years.Based on previous work,this inter-annual variation pattern was deduced to be caused by dynamic processes.In further work on the regulatory mechanisms,empirical orthogonal function(EOF)decomposition was performed.It was found that the modes of the dispersion coefficient have different geographical distributions,explaining the reason why the wave components in different frequencies appeared in different locations.The numerical simulation results confirm that the variations in the parameters of the ISWs derived from the eKdV equation could affect the waveforms significantly because of changes in the polarity of the ISWs.Therefore,the periodic variations of the dynamic parameters are related to the geographical location because of dynamic processes operating. 展开更多
关键词 internal solitary waves(ISWs) dynamic parameters eKdV equation spatiotemporal variation polarity empirical orthogonal function(EOF)decomposition
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基于EEMD、相关系数、排列熵和小波阈值去噪的新型水下声学信号去噪方法
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作者 张玉燕 杨志霞 +1 位作者 杜晓莉 罗小元 《哈尔滨工程大学学报(英文版)》 CSCD 2024年第1期222-237,共16页
The complexities of the marine environment and the unique characteristics of underwater channels pose challenges in obtaining reliable signals underwater,necessitating the filtration of underwater acoustic noise.Herei... The complexities of the marine environment and the unique characteristics of underwater channels pose challenges in obtaining reliable signals underwater,necessitating the filtration of underwater acoustic noise.Herein,an underwater acoustic signal denoising method based on ensemble empirical mode decomposition(EEMD),correlation coefficient(CC),permutation entropy(PE),and wavelet threshold denoising(WTD)is proposed.Furthermore,simulation experiments are conducted using simulated and real underwater acoustic data.The experimental results reveal that the proposed denoising method outperforms other previous methods in terms of signal-to-noise ratio,root mean square error,and CC.The proposed method eliminates noise and retains valuable information in the signal. 展开更多
关键词 Ensemble empirical mode decomposition Correlation coefficient Permutation entropy Wavelet threshold denoising Underwater acoustic signal denoising
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Incorporating empirical knowledge into data-driven variable selection for quantitative analysis of coal ash content by laser-induced breakdown spectroscopy
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作者 吕一涵 宋惟然 +1 位作者 侯宗余 王哲 《Plasma Science and Technology》 SCIE EI CAS CSCD 2024年第7期148-156,共9页
Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can a... Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can affect its quantification performance.In this work,we propose a hybrid variable selection method to improve the performance of LIBS quantification.Important variables are first identified using Pearson's correlation coefficient,mutual information,least absolute shrinkage and selection operator(LASSO)and random forest,and then filtered and combined with empirical variables related to fingerprint elements of coal ash content.Subsequently,these variables are fed into a partial least squares regression(PLSR).Additionally,in some models,certain variables unrelated to ash content are removed manually to study the impact of variable deselection on model performance.The proposed hybrid strategy was tested on three LIBS datasets for quantitative analysis of coal ash content and compared with the corresponding data-driven baseline method.It is significantly better than the variable selection only method based on empirical knowledge and in most cases outperforms the baseline method.The results showed that on all three datasets the hybrid strategy for variable selection combining empirical knowledge and data-driven algorithms achieved the lowest root mean square error of prediction(RMSEP)values of 1.605,3.478 and 1.647,respectively,which were significantly lower than those obtained from multiple linear regression using only 12 empirical variables,which are 1.959,3.718 and 2.181,respectively.The LASSO-PLSR model with empirical support and 20 selected variables exhibited a significantly improved performance after variable deselection,with RMSEP values dropping from 1.635,3.962 and 1.647 to 1.483,3.086 and 1.567,respectively.Such results demonstrate that using empirical knowledge as a support for datadriven variable selection can be a viable approach to improve the accuracy and reliability of LIBS quantification. 展开更多
关键词 laser-induced breakdown spectroscopy(LIBS) coal ash content quantitative analysis variable selection empirical knowledge partial least squares regression(PLSR)
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Anisotropic shearing mechanism of Kangding slate:Experimental investigation and numerical analysis
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作者 Ping Liu Quansheng Liu +4 位作者 Penghai Deng Yucong Pan Yiming Lei Chenglei Du Xianqi Xie 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2024年第5期1487-1504,共18页
The shear mechanical behavior is regarded as an essential factor affecting the stability of the surrounding rocks in underground engineering.The shear strength and failure mechanisms of layered rock are significantly ... The shear mechanical behavior is regarded as an essential factor affecting the stability of the surrounding rocks in underground engineering.The shear strength and failure mechanisms of layered rock are significantly affected by the foliation angles.Direct shear tests were conducted on cubic slate samples with foliation angles of 0°,30°,45°,60°,and 90°.The effect of foliation angles on failure patterns,acoustic emission(AE)characteristics,and shear strength parameters was analyzed.Based on AE characteristics,the slate failure process could be divided into four stages:quiet period,step-like increasing period,dramatic increasing period,and remission period.A new empirical expression of cohesion for layered rock was proposed,which was compared with linear and sinusoidal cohesion expressions based on the results made by this paper and previous experiments.The comparative analysis demonstrated that the new expression has better prediction ability than other expressions.The proposed empirical equation was used for direct shear simulations with the combined finite-discrete element method(FDEM),and it was found to align well with the experimental results.Considering both computational efficiency and accuracy,it was recommended to use a shear rate of 0.01 m/s for FDEM to carry out direct shear simulations.To balance the relationship between the number of elements and the simulation results in the direct shear simulations,the recommended element size is 1 mm. 展开更多
关键词 ANISOTROPY Empirical expression of cohesion foliation angles Combined finite-discrete element method(FDEM) Shear rate Element size
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Long-term ocean temperature trend and marine heatwaves
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作者 Min ZHANG Yangyan CHENG +4 位作者 Gang WANG Qi SHU Chang ZHAO Yuanling ZHANG Fangli QIAO 《Journal of Oceanology and Limnology》 SCIE CAS CSCD 2024年第4期1037-1047,共11页
Marine heatwaves(MHWs)can cause irreversible damage to marine ecosystems and livelihoods.Appropriate MHW characterization remains difficult,because the choice of a sea surface temperature(SST)temporal baseline strongl... Marine heatwaves(MHWs)can cause irreversible damage to marine ecosystems and livelihoods.Appropriate MHW characterization remains difficult,because the choice of a sea surface temperature(SST)temporal baseline strongly influences MHW identification.Following a recent work suggesting that there should be a communicating baseline for long-term ocean temperature trends(LTT)and MHWs,we provided an effective and quantitative solution to calculate LTT and MHWs simultaneously by using the ensemble empirical mode decomposition(EEMD)method.The long-term nonlinear trend of SST obtained by EEMD shows superiority over the traditional linear trend in that the data extension does not alter prior results.The MHWs identified from the detrended SST data exhibited low sensitivity to the baseline choice,demonstrating the robustness of our method.We also derived the total heat exposure(THE)by combining LTT and MHWs.The THE was sensitive to the fixed-period baseline choice,with a response to increasing SST that depended on the onset time of a perpetual MHW state(identified MHW days equal to the year length).Subtropical areas,the Indian Ocean,and part of the Southern Ocean were most sensitive to the long-term global warming trend. 展开更多
关键词 marine heatwaves(MHWs) ensemble empirical mode decomposition(EEMD) long-term temperature(LTT)trend total heat exposure(THE)
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Research on Early Warning of Banking Crises from the Perspective of Credit Structures
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作者 Zhou Yuqin Luo Zixuan Wu Shan 《Contemporary Social Sciences》 2024年第3期45-63,共19页
The relationship between credit expansion and banking crises is complex and cannot be fully explained by total credit alone.A systematic analysis of the relationship between the amount and structure of total credit an... The relationship between credit expansion and banking crises is complex and cannot be fully explained by total credit alone.A systematic analysis of the relationship between the amount and structure of total credit and banking crises is important for an objective prediction of the influence of potential financial risks.This paper,drawing on data from 15 selected countries,delves into the power of credit indicators in the early warning of banking crises from the perspectives of industrial structure,sector structure,and term structure of credit.Various machine learning methods were used,including Logistic Regression,Random Forest,Decision Tree,Support Vector Machine(SVM),Bagging,and Boosting models.The empirical findings indicate that credit expansion plays a crucial role in triggering banking crises.However,total credit is better suited for the early warning of short-term banking crises,whereas credit structure is more useful for the early warning of long-term banking crises.Moreover,in an early warning system,identifying key early warning indicators is more meaningful than merely increasing the number of indicators.Machine learning can somewhat enhance the early warning power,but it may not always be robust.Therefore,more attention should be paid to potential systemic banking crises resulting from an imbalance in credit structure while regulating the total credit threshold. 展开更多
关键词 banking crises credit expansion transnational empirical evidence structural perspective
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Fault DiagnosisMethod of Energy Storage Unit of Circuit Breakers Based on EWT-ISSA-BP
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作者 Tengfei Li Wenhui Zhang +3 位作者 Ke Mi Qingming Lin Shuangwei Zhao Jiayi Song 《Energy Engineering》 EI 2024年第7期1991-2007,共17页
Aiming at the problem of energy storage unit failure in the spring operating mechanism of low voltage circuit breakers(LVCBs).A fault diagnosis algorithm based on an improved Sparrow Search Algorithm(ISSA)optimized Ba... Aiming at the problem of energy storage unit failure in the spring operating mechanism of low voltage circuit breakers(LVCBs).A fault diagnosis algorithm based on an improved Sparrow Search Algorithm(ISSA)optimized Backpropagation Neural Network(BPNN)is proposed to improve the operational safety of LVCB.Taking the 1.5kV/4000A/75kA LVCB as an example.According to the current operating characteristics of the energy storage motor,fault characteristics are extracted based on Empirical Wavelet Transform(EWT).Traditional BPNN has problems such as difficulty adjusting network weights and thresholds,being sensitive to initial weights,and quickly falling into local optimal solutions.The Sparrow Search Algorithm(SSA)with self-adjusting weight factors combined with bidirectional mutations is added to optimize the selection of BPNN hyperparameters.The results show that the ISSA-BPNN can accurately and quickly distinguish six conditions of motor voltage reduction:motor voltage increase,motor voltage decrease,energy storage spring stuck,transmission gear stuck,regular state and energy storage spring not locked.It is suitable for fault diagnosis and detection of the energy storage part of LVCB. 展开更多
关键词 Low voltage circuit breakers energy storage motor current sparrow search algorithm empirical wavelet transform fault diagnosis
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Retrospective study of the incidence, risk factors, treatment outcomes of bacterial infections at uncommon sites in cirrhotic patients
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作者 Sophie Schneitler Christina Schneider +4 位作者 Markus Casper Frank Lammert Marcin Krawczyk Sören L Becker Matthias Christian Reichert 《World Journal of Hepatology》 2024年第3期418-427,共10页
BACKGROUND Bacterial infections(BI)negatively affect the natural course of cirrhosis.The most frequent BI are urinary tract infections(UTI),pneumonia,and spontaneousbacterial peritonitis(SBP).AIM To assess the relevan... BACKGROUND Bacterial infections(BI)negatively affect the natural course of cirrhosis.The most frequent BI are urinary tract infections(UTI),pneumonia,and spontaneousbacterial peritonitis(SBP).AIM To assess the relevance of bacterial infections beyond the commonly recognized types in patients with cirrhosis and to investigate their relationship with other clinical variables.METHODS We retrospectively analyzed patients with cirrhosis and BI treated between 2015 and 2018 at our tertiary care center.BIs were classified as typical and atypical,and clinical as well as laboratory parameters were compared between the two groups.RESULTS In a cohort of 488 patients with cirrhosis,we identified 225 typical BI(95 UTI,73 SBP,72 pulmonary infections)and 74 atypical BIs,predominantly cholangitis and soft tissue infections(21 each),followed by intra-abdominal BIs(n=9),cholecystitis(n=6),head/throat BIs(n=6),osteoarticular BIs(n=5),and endocarditis(n=3).We did not observe differences concerning age,sex,or etiology of cirrhosis in patients with typical vs atypical BI.Atypical BIs were more common in patients with more advanced cirrhosis,as evidenced by Model of End Stage Liver Disease(15.1±7.4 vs 12.9±5.1;P=0.005)and Child-Pugh scores(8.6±2.5 vs 8.0±2;P=0.05).CONCLUSION Atypical BIs in cirrhosis patients exhibit a distinct spectrum and are associated with more advanced stages of the disease.Hence,the work-up of cirrhosis patients with suspected BI requires detailed work-up to elucidate whether typical BI can be identified. 展开更多
关键词 Bacterial infection Empirical antibiotic therapy End-stage liver disease Escherichia coli Multi-resistant pathogens
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基于CEEMDAN-HT的永磁同步电机匝间短路振动信号故障特征提取研究
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作者 夏焰坤 李欣洋 +1 位作者 任俊杰 寇坚强 《振动与冲击》 EI CSCD 北大核心 2024年第5期72-81,共10页
由于长时间处于高负荷运行状态,永磁同步电机(permanent magnet synchronous motor, PMSM)定子绕组线圈匝与匝之间的绝缘性能容易降低,导致出现匝间短路,此时电机的振动强度会发生改变。针对此现象,提出将自适应噪声完备经验模态分解(co... 由于长时间处于高负荷运行状态,永磁同步电机(permanent magnet synchronous motor, PMSM)定子绕组线圈匝与匝之间的绝缘性能容易降低,导致出现匝间短路,此时电机的振动强度会发生改变。针对此现象,提出将自适应噪声完备经验模态分解(complete ensemble empirical mode decomposition with adaptive noise, CEEMDAN)与希尔伯特变换(Hilbert transform, HT)结合,构成一种CEEMDAN-HT非线性信号分析方法,并将其应用于提取振动信号故障特征。首先,利用CEEMDAN算法分解振动信号,得到一系列本征模态函数(intrinsic mode function, IMF),并将主元分析中的方差贡献率用于识别包含故障特征信息的IMF。其次,使用HT对方差贡献率较高的IMF进行分析,并以三维联合时频图呈现时间、瞬时频率与幅值,得到了主要故障特征。最后,使用ANSYS有限元软件建立了电机短路故障模型,并搭建了短路故障试验平台,通过对比有限元仿真结果与试验结果,对提出的方法进行了有效性和准确性验证。 展开更多
关键词 永磁同步电机(permanent magnet synchronous motor PMSM) 振动信号 自适应噪声完备经验模态分解(complete ensemble empirical mode decomposition with adaptive noise CEEMDAN) 特征提取 希尔伯特变换(Hilbert transform HT)
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Modeling the Kinetics of Moisture Desorption from Safou Pulp [Dacryodes edulis (G. Don) H.J.Lam] before the Oil Extraction Step
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作者 Anicet Frédéric Binaki Feueltgaldah Christian Bopoundza +3 位作者 Bob Wilfrid Loumouamou Gueko Séraphin Nguié Eliane Thérèse Biassala Thomas Silou 《Open Journal of Applied Sciences》 2024年第8期2050-2064,共15页
The aim of this work is to model the drying kinetics of Safou pulp with or without endocarp using a phenomenological approach. Oven-drying kinetics at 70˚C, 90˚C and 105˚C were monitored using the curves given by the ... The aim of this work is to model the drying kinetics of Safou pulp with or without endocarp using a phenomenological approach. Oven-drying kinetics at 70˚C, 90˚C and 105˚C were monitored using the curves given by the reduced mass as a function of time, which are modeled according to the Avrami/page, Fick and Peleg models using OringinPro 2018 software. The results showed that parameters k and n of the Avrami/Page model vary very little with fruit size and drying temperature (0.0018 ± 0.0002 k n k (Avrami model/page) were virtually identical, while b (Fick model) and n (Avrami model/page) were virtually identical for the same sample. For the Peleg model, the parameter a, varies from 0.0018 ± 0.0002 to 0.03328 ± 0.0079, with a ratio of 18.6 for all experimental conditions studied. However, with 0.977 R2 χ2 < 0.00002, we have a good fit of the model to the experimental data. The same applies to parameter b, which ranges from 0.82 ± 0.05 to 1.21 ± 0.02. Thus, drying modeling by these three models can be used to describe and predict the progress of oven-drying of safou pulp. 展开更多
关键词 DRYING MODELING Empirical Models Dacryodes edulis Congo Basin
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