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Comparison of Different IFORM-Based Methods for Long-Term Extreme Response Estimation of Floating Offshore Wind Turbines 认领 引用
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作者 ZHAO Guanhua DONG Sheng 《Journal of Ocean University of China》 SCIE CAS CSCD 2026年第4期1227-1244,共18页
Estimating extreme responses is crucial in the design of floating offshore wind turbines(FOWTs).The responses of an FOWT are neither continuous nor monotonic,as the turbine operates exclusively within the range from t... Estimating extreme responses is crucial in the design of floating offshore wind turbines(FOWTs).The responses of an FOWT are neither continuous nor monotonic,as the turbine operates exclusively within the range from the cut-in to the cut-out wind speeds.Consequently,the traditional environmental contour method(ECM)may be unsuitable for evaluating the long-term extreme responses of FOWTs.This paper introduces a four-dimensional(4D)inverse first-order reliability method(IFORM)that combines ECM with a surrogate model.This combination explicitly accounts for environmental conditions and response variability.The dependence structure of multidimensional environmental conditions was modeled using a C-vine copula and marginal mixture distributions.Several long-term extreme response estimation methods,including 4D IFORM,ECM,the modified ECM,and the full long-term analysis,were tested on the OC4 DeepCwind NREL 5MW semisubmersible wind turbine.Because the accurate estimation of long-term extreme responses is greatly dependent on performing a large number of numerical simulations,the implementation of these methods becomes quite challenging.In this study,the surrogate model was used to rapidly calculate environmental condition parameters and short-term extreme responses.The applicability of these load assessment models was demonstrated and discussed by considering the extreme tension of the mooring line and the tower base pitching moment of the FOWT. 展开更多
关键词 floating offshore wind turbine long-term extreme response environmental contour method 4D inverse first-order reliability method surrogate model
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A cascaded pipeline defect detection and size estimation method based on the YOLOv11 and physics-informed network using the MFL data 认领 引用 被引量：1
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作者 Xi-Ming Chen Meng-Kai Fu +1 位作者 Jia Shao Xiao-Ben Liu 《Petroleum Science》 SCIE EI CAS CSCD 2026年第3期1505-1518,共14页
Long-distance oil and gas pipelines are crucial in the global energy network.However,due to complex internal and external environments,defects can be formed on a pipeline's surface,posing severe threats to structu... Long-distance oil and gas pipelines are crucial in the global energy network.However,due to complex internal and external environments,defects can be formed on a pipeline's surface,posing severe threats to structural safety.Aiming to detect surface defects,recent works have used magnetic flux leakage(MFL) inspection data for defect recognition and defect size estimation.Accurately locating and measuring defects based on the MFL data is essential for pipeline integrity assessment and safety maintenance.To obtain effective MFL data on pipeline defects,this study constructs an experimental pipeline at the Daxing pulling-through test site in Beijing.An ultra-high-definition MFL inspection robot is employed to collect defect data,which are then used to construct a defect detection and size estimation database.In addition,to achieve precise defect recognition and quantification,a cascaded method,which integrates a mature computer vision detection model,the YOLOv11 model,with a physics-informed and data-driven prior deep-learning quantification model,is proposed.Validation results show that,even for a limited amount of data,the proposed defect recognition model can achieve an AP50 of 92.1% at a confidence threshold of 0.6,a precision of 100%,a recall of 84.29%,and an F1-score of 91.47 %,indicating high accuracy in identifying surface defects on pipelines.The quantification model can achieve the goodness of fit(Gof) values of 0.987,0.979,and 0.994 for defect length,width,and depth,with the mean absolute percentage error(MAPE) of 7.97%,8.52%,and 4.74%,respectively.Comparison analysis with different models confirms the superiority of the proposed cascaded recognition and quantification approach.The results also demonstrate that the proposed method can effectively identify and quantify defects in long-distance pipelines.Finally,it can improve the interpretation efficiency of MFL inspection data and provide reliable support for residual strength assessment and remaining life prediction of pipelines. 展开更多
关键词 Oil and gas pipeline MFL inspection Defect detection Defect size estimation
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Normal vector estimation method for rock mass point clouds with sharp feature preservation via local geometric adjustment 认领 引用
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作者 Mingming Ren Manchao He +4 位作者 Jie Hu Hongru Li Yuxiang Ding Xinhao Miao Hongyi Zhang 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2026年第5期3722-3741,共20页
Accurate extraction of rock mass discontinuity parameters is crucial for stability assessment and engineering safety.High-resolution remote sensing facilitates automated extraction,but its effectiveness relies heavily... Accurate extraction of rock mass discontinuity parameters is crucial for stability assessment and engineering safety.High-resolution remote sensing facilitates automated extraction,but its effectiveness relies heavily on precise normal estimation to ensure geometric reliability.Conventional methods struggle to preserve sharp features such as edges and corners,thereby reducing accuracy.To address this,we propose a normal estimation method based on local geometric adjustment that enhances feature extraction while maintaining sharp geometries.The approach consists of four steps:(1)classifying points,(2)applying normal and axial projections,(3)fitting segmentation lines via least squares,and(4)refining normals by optimizing local neighborhoods.The proposed method was evaluated on computer-aided design(CAD)models,real objects,and rock mass point clouds,and benchmarked against eight representative algorithms,including principal component analysis(PCA),2-Jet PCA,Voronoi-based PCA,PCPNet,neural gradient function(NeuralGF),low rank representation(LRR),normal estimation via shifted neighborhood(NSN)and pair consistency voting(PCV).Experimental results demonstrate that our method achieves superior accuracy and efficiency,significantly improving structural plane extraction and ensuring better preservation of sharp geometric features. 展开更多
关键词 Rock mass point cloud Normal vector estimation Sharp feature Rock engineering
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DOA estimation via a Newton-like method under unknown mutual coupling 认领 引用
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作者 LYU Jihui LIU Shuai +2 位作者 JIN Ming YAN Fenggang SONG Lizhong 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2026年第3期826-835,共10页
As is well known,mutual coupling between array elements has a significant negative impact on direction of arrival(DOA)estimation.To achieve DOA estimation under unknown mutual coupling,this paper proposes a low comput... As is well known,mutual coupling between array elements has a significant negative impact on direction of arrival(DOA)estimation.To achieve DOA estimation under unknown mutual coupling,this paper proposes a low computational complexity Newton-like method.Firstly,a block sparse model based on the signal subspace is established,and the Lagrangian function is established according to the block sparse model.Secondly,since the Hessian matrix of the Lagrangian function cannot always ensure positive definiteness and the computational complexity of the inverse matrix of the Hessian matrix is enormous,the Newton method is no longer applicable.Therefore,this paper proposes a Newton-like method to achieve DOA estimation under mutual coupling and reduce the computational complexity by matrix inversion lemma.Finally,compared with existing methods of DOA estimation under array mutual coupling,the simulation results validate the effectiveness of the proposed method. 展开更多
关键词 direction of arrival(DOA) mutual coupling block sparse Newton-like method
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Sparse DOA Estimation Method for Unknown Terrestrial Signals of Opportunity 认领 引用
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作者 TANG Zewen LANG Rongling XU Hao 《Journal of Shanghai Jiaotong university(Science)》 EI 2026年第4期858-868,I0004,共11页
Signal of opportunity(SOP)has become an attractive source of navigation in the absence of global navigation satellite system(GNSS).However,in some typical GNSS-limited environments,such as deep urban canyons,the SOP p... Signal of opportunity(SOP)has become an attractive source of navigation in the absence of global navigation satellite system(GNSS).However,in some typical GNSS-limited environments,such as deep urban canyons,the SOP positioning is challenged by low signal-to-noise ratio(SNR),rapidly time-varying channels,and gain/phase uncertainties.To overcome these challenges,we propose a sparse direction of arrival(DOA)estimation method specifically designed for SOP positioning.Under the conditions of low SNR and limited number of snapshots,we conduct detailed theoretical derivations and simulation experiments to analyze the negative impact of gain and phase uncertainties on sparse DOA estimation.The analysis indicates that these uncertainties can lead to an increase in the number or height of spurious peaks in the DOA spatial spectrum,thereby significantly reducing the accuracy of DOA estimation.To address this issue,we propose a non-iterative sparse DOA estimation method that combines blind source separation(BSS)and singular value decomposition(SVD)techniques.The BSS algorithm accurately determines the number of SOPs using a single sensor,effectively eliminating the impact of gain and phase uncertainties between sensors.Once the number of SOPs is obtained,we can introduce the SVD algorithm to further enhance the DOA estimation performance under low SNR conditions.Simulation results validate the effectiveness of the proposed method in DOA estimation,showcasing its excellent robustness and self-calibration characteristics while maintaining reasonable computational costs.The introduction of this method provides a new solution to the navigation and positioning problem in GNSS-denied environments. 展开更多
关键词 signal of opportunity(SOP) direction of arrival estimation(DOA) gain and phase uncertainties sparse reconstruction self-calibration
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Sensitivity-based state and parameter moving horizon estimation method for liquid propellant rocket engine 认领 引用
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作者 Zizhao WANG Dan WANG +2 位作者 Hongyu CHEN Zhijiang SHAO Zhengyu SONG 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2025年第7期46-60,共15页
The reuse of liquid propellant rocket engines has increased the difficulty of their control and estimation.State and parameter Moving Horizon Estimation(MHE)is an optimization-based strategy that provides the necessar... The reuse of liquid propellant rocket engines has increased the difficulty of their control and estimation.State and parameter Moving Horizon Estimation(MHE)is an optimization-based strategy that provides the necessary information for model predictive control.Despite the many advantages of MHE,long computation time has limited its applications for system-level models of liquid propellant rocket engines.To address this issue,we propose an asynchronous MHE method called advanced-multi-step MHE with Noise Covariance Estimation(amsMHE-NCE).This method computes the MHE problem asynchronously to obtain the states and parameters and can be applied to multi-threaded computations.In the background,the state and covariance estimation optimization problems are computed using multiple sampling times.In real-time,sensitivity is used to quickly approximate state and parameter estimates.A covariance estimation method is developed using sensitivity to avoid redundant MHE problem calculations in case of sensor degradation during engine reuse.The amsMHE-NCE is validated through three cases based on the space shuttle main engine system-level model,and we demonstrate that it can provide more accurate real-time estimates of states and parameters compared to other commonly used estimation methods. 展开更多
关键词 Sensitivity Moving horizon estimation Noise covariance estimation Parameter estimation Liquid propellant rocket engine
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The estimation method is the primary source of uncertainty in cropland nitrate leaching estimates in China 认领 引用
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作者 Xingshuai Tian Huitong Yu +4 位作者 Jiahui Cong Yulong Yin Kai He Zihan Wang Zhenling Cui 《Journal of Integrative Agriculture》 SCIE CAS CSCD 2025年第6期2425-2437,共13页
Cropland nitrate leaching is the major nitrogen(N) loss pathway, and it contributes significantly to water pollution. However, cropland nitrate leaching estimates show great uncertainty due to variations in input data... Cropland nitrate leaching is the major nitrogen(N) loss pathway, and it contributes significantly to water pollution. However, cropland nitrate leaching estimates show great uncertainty due to variations in input datasets and estimation methods. Here, we presented a re-evaluation of Chinese cropland nitrate leaching, and identified and quantified the sources of uncertainty by integrating three cropland area datasets, three N input datasets, and three estimation methods. The results revealed that nitrate leaching from Chinese cropland averaged 6.7±0.6 Tg N yr-1in 2010, ranging from 2.9 to 15.8 Tg N yr-1across 27 different estimates. The primary contributor to the uncertainty was the estimation method, accounting for 45.1%, followed by the interaction of N input dataset and estimation method at 24.4%. The results of this study emphasize the need for adopting a robust estimation method and improving the compatibility between the estimation method and N input dataset to effectively reduce uncertainty. This analysis provides valuable insights for accurately estimating cropland nitrate leaching and contributes to ongoing efforts that address water pollution concerns. 展开更多
关键词 cropland nitrate leaching uncertainty cropland area nitrogen input estimation method
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High-Precision Fish Pose Estimation Method Based on Improved HRNet 认领 引用 被引量：1
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作者 PENG Qiujun LI Weiran +1 位作者 LIU Yeqiang LI Zhenbo 《智慧农业（中英文）》 CSCD 2025年第3期160-172,共13页
[Objective]Fish pose estimation(FPE)provides fish physiological information,facilitating health monitoring in aquaculture.It aids decision-making in areas such as fish behavior recognition.When fish are injured or def... [Objective]Fish pose estimation(FPE)provides fish physiological information,facilitating health monitoring in aquaculture.It aids decision-making in areas such as fish behavior recognition.When fish are injured or deficient,they often display abnormal behaviors and noticeable changes in the positioning of their body parts.Moreover,the unpredictable posture and orientation of fish during swimming,combined with the rapid swimming speed of fish,restrict the current scope of research in FPE.In this research,a FPE model named HPFPE is presented to capture the swimming posture of fish and accurately detect their key points.[Methods]On the one hand,this model incorporated the CBAM module into the HRNet framework.The attention module enhanced accuracy without adding computational complexity,while effectively capturing a broader range of contextual information.On the other hand,the model incorporated dilated convolution to increase the receptive field,allowing it to capture more spatial context.[Results and Discussions]Experiments showed that compared with the baseline method,the average precision(AP)of HPFPE based on different backbones and input sizes on the oplegnathus punctatus datasets had increased by 0.62,1.35,1.76,and 1.28 percent point,respectively,while the average recall(AR)had also increased by 0.85,1.50,1.40,and 1.00,respectively.Additionally,HPFPE outperformed other mainstream methods,including DeepPose,CPM,SCNet,and Lite-HRNet.Furthermore,when compared to other methods using the ornamental fish data,HPFPE achieved the highest AP and AR values of 52.96%,and 59.50%,respectively.[Conclusions]The proposed HPFPE can accurately estimate fish posture and assess their swimming patterns,serving as a valuable reference for applications such as fish behavior recognition. 展开更多
关键词 aquaculture computer vision fish pose estimation key point attention mechanism
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Dynamic Vision-Enabled Intelligent Micro-Vibration Estimation Method with Spatiotemporal Pattern Consistency 认领 引用 被引量：1
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作者 Shupeng Yu Xiang Li +2 位作者 Yaguo Lei Bin Yang Naipeng Li 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2025年第11期2359-2361,共3页
Dear Editor,This letter proposes a novel dynamic vision-enabled intelligent micro-vibration estimation method with spatiotemporal pattern consistency.Inspired by biological vision,dynamic vision data are collected by ... Dear Editor,This letter proposes a novel dynamic vision-enabled intelligent micro-vibration estimation method with spatiotemporal pattern consistency.Inspired by biological vision,dynamic vision data are collected by the event camera,which is able to capture the micro-vibration information of mechanical equipment,due to the significant advantage of extremely high temporal sampling frequency. 展开更多
关键词 dynamic vision micro vibration mechanical equipmentdue spatiotemporal pattern consistency biological visiondynamic vision data intelligent estimation event camera event camerawhich
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Radar Micro-Doppler Parameter Estimation Method Based on Gated Dual-Path Dynamic-Wavelet Convolutional Network 认领 引用
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作者 Jinhao Wang Xiaolong Chen +2 位作者 Xinghai Wang Jian Guan Xiaolin Du 《Journal of Beijing Institute of Technology》 EI CAS 2025年第6期566-576,共11页
Micro-Doppler parameter estimation is crucial for moving targets.However,conventional methods face limitations like inadequate time-frequency(TF)resolution and poor generalization,while existing deep learning approach... Micro-Doppler parameter estimation is crucial for moving targets.However,conventional methods face limitations like inadequate time-frequency(TF)resolution and poor generalization,while existing deep learning approaches often treat TF analysis as a fixed preprocessing step.To overcome these challenges,this paper introduces a radar micro-Doppler parameter estimation method based on a gated dual-path dynamic-wavelet convolutional network(GDWCN).The GDWCN is an end-to-end deep learning framework that maps raw radar signals to micro-motion parameters by integrating clutter suppression,gated dual-path module,feature extraction,and parameter regression.Its core innovation is a gated dual-path module that combines dynamic convolution and learnable wavelet convolution,selecting the optimal processing path based on input signal characteristics.For the Inspire 2 drone,GDWCN reduced the mean absolute error(MAE)of frequency estimation by approximately 38%compared to the enhanced time-frequency micro-Doppler network,and its relative error by approximately 69%compared to the short-time Fourier transform(STFT),and 58%over the local maximum synchroextracting transform.Ablation studies further confirm the efficacy of the clutter suppression module and the attention mechanism. 展开更多
关键词 parameter estimation radar signal processing deep learning time-frequency analysis
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A thrust estimation and control method of an adaptive cycle engine based on improved MFAC algorithm 认领 引用
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作者 Xin ZHOU Wenjuan CHEN +2 位作者 Jinquan HUANG Jingtian LIU Feng LU 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2025年第5期182-201,共20页
The development of the adaptive cycle engine is a crucial direction of advanced fighter power sources in the near future.However,this new technology brings more uncertainty to the design of the control system.To addre... The development of the adaptive cycle engine is a crucial direction of advanced fighter power sources in the near future.However,this new technology brings more uncertainty to the design of the control system.To address the versatile thrust demand under complex dynamic characteristics of the adaptive cycle engine,this paper proposes a direct thrust estimation and control method based on the Model-Free Adaptive Control(MFAC)algorithm.First,an improved Sliding Mode Control-MFAC(SMC-MFAC)algorithm has been developed by introducing a sliding mode variable structure into the standard Full Format Dynamic Linearization-MFAC(FFDL-MFAC)and designing self-adaptive weight coefficients.Then a trivariate double-loop direct thrust control structure with a controller-based thrust estimator and an outer command compensation loop has been established.Through thrust feedback and command correction,accurate control under multi-mode and operation conditions is achieved.The main contribution of this paper is the improved algorithm that combines the tracking capability of the MFAC and the robustness of the SMC,thus enhancing the dynamic performance.Considering the requirements of the online thrust feedback,the designed MFAC-based thrust estimator significantly speeds up the calculation.Additionally,the proposed command correction module can achieve the adaptive thrust control without affecting the operation of the inner loop.Simulations and Hardware-in-Loop(HIL)experiments have been performed on an adaptive cycle engine component-level model to investigate the estimation and control effect under different modes and health conditions.The results demonstrate that both the thrust estimation precision and operation speed are significantly improved compared with Extended Kalman Filter(EKF).Furthermore,the system can accelerate the response of the controlled plant,reduce the overshoot,and realize the thrust recovery within the safety range when the engine encounters the degradation. 展开更多
关键词 Adaptivecycle engine Direct thrust control Model-free adaptive control Sliding mode control Thrust estimation
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Fault Distance EstimationMethod for DC Distribution Networks Based on Sparse Measurement of High-Frequency Electrical Quantities 认领 引用
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作者 He Wang Shiqiang Li +1 位作者 Yiqi Liu Jing Bian 《Energy Engineering》 EI 2025年第11期4497-4521,共25页
With the evolution of DC distribution networks from traditional radial topologies to more complex multi-branch structures,the number of measurement points supporting synchronous communication remains relatively limite... With the evolution of DC distribution networks from traditional radial topologies to more complex multi-branch structures,the number of measurement points supporting synchronous communication remains relatively limited.This poses challenges for conventional fault distance estimation methods,which are often tailored to simple topologies and are thus difficult to apply to large-scale,multi-node DC networks.To address this,a fault distance estimation method based on sparse measurement of high-frequency electrical quantities is proposed in this paper.First,a preliminary fault line identification model based on compressed sensing is constructed to effectively narrow the fault search range and improve localization efficiency.Then,leveraging the high-frequency impedance characteristics and the voltage-current relationship of electrical quantities,a fault distance estimation approach based on high-frequency measurements from both ends of a line is designed.This enables accurate distance estimation even when the measurement devices are not directly placed at both ends of the faulted line,overcoming the dependence on specific sensor placement inherent in traditional methods.Finally,to further enhance accuracy,an optimization model based on minimizing the high-frequency voltage error at the fault point is introduced to reduce estimation error.Simulation results demonstrate that the proposed method achieves a fault distance estimation error of less than 1%under normal conditions,and maintains good performance even under adverse scenarios. 展开更多
关键词 DC distribution network fault location compressed sensing fault distance estimation high-frequency electrical quantities
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Power System State Estimation Solution With Zero Injection Constraints Using Modified Newton Method and Fast Decoupled Method in Polar Coordinate 认领 引用 被引量：14
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作者 GUO Ye ZHANG Boming +1 位作者 WU Wenchuag SUN Hongbin 《中国电机工程学报》 EI CSCD 北大核心 2012年第22期I0015-I0015,11,共1页
In actual power systems,most of the high-voltage buses of the transformers are zero injection buses without load or generation.Power injections into these buses are strictly 0,so based on Kirchhoff's current law(K... In actual power systems,most of the high-voltage buses of the transformers are zero injection buses without load or generation.Power injections into these buses are strictly 0,so based on Kirchhoff's current law(KCL),equality constraints should be used to handle these buses in a state estimation model.It is a challenge to ensure that these zero injection constraints can be strictly satisfied without losing computational efficiency. 展开更多
关键词 state estimation zero injection equality constraints polar coordinate modified Newton method modified fast decoupled state estimation
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Soil Bulk Density Estimation Methods: A Review 认领 引用 被引量：18
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作者 Ahmed Abed Gatea AL-SHAMMARY Abbas Z.KOUZANI +3 位作者 Akif KAYNAK Sui Yang KHOO Michael NORTON Will GATES 《Pedosphere》 SCIE CAS CSCD 2018年第4期581-596,共16页
Measurement of soil bulk density is important for understanding the physical, chemical, and biological properties of soil. Accurate and rapid soil bulk density measurement techniques play a significant role in agricul... Measurement of soil bulk density is important for understanding the physical, chemical, and biological properties of soil. Accurate and rapid soil bulk density measurement techniques play a significant role in agricultural experimental research. This review is a comprehensive summary of existing measurement methods and evaluates their advantages, disadvantages, potential sources of error,and directions for future development. These techniques can be broadly categorised as direct and indirect methods. Direct methods include core, clod, and excavation sampling, whereas indirect methods include the radiation and regression approaches. The core method is most widely used, but it is time consuming and difficult to use for sampling multiple soil depths. The size of the coring cylinder used, operator experience, sampling depth, and in-situ soil moisture content significantly affect its accuracy. The clod method is suitable for use with heavy clay soils, and its accuracy is dependent on equipment calibration, drying time, and operator experience, but the process is complicated and time consuming. Excavation techniques are most commonly used to evaluate the bulk density of forest soils, but have major limitations as they cannot be used in soils with large pores and their measurement accuracy is strongly influenced by soil texture and the type of analysis selected. The indirect methods appear to have greater accuracy than direct approaches, but have higher costs, are more complex, and require greater operator experience. One such approach uses gamma radiation, and its accuracy is strongly influenced by soil depth. Regression methods are economical as they can make indirect measurements, but these depend on good, quality data of soil texture and organic matter content and geographical and climatic properties. Also, like most of the other approaches, its accuracy decreases with sampling depth. 展开更多
关键词 measurement accuracy direct measurement methods gamma radiation indirect measurement methods regression methods sampling depth soil properties
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Evaluation of estimation methods for meiofaunal biomass from a meiofaunal survey in Bohai Bay 认领 引用 被引量：5
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作者 张青田 王新华 胡桂坤 《Chinese Journal of Oceanology and Limnology》 2010年第1期82-87,共6页
Studies in the coastal area of Bohai Bay,China,from July 2006 to October 2007,suggest that the method of meiofaunal biomass estimation affected the meiofaunal analysis.Conventional estimation methods that use a unique... Studies in the coastal area of Bohai Bay,China,from July 2006 to October 2007,suggest that the method of meiofaunal biomass estimation affected the meiofaunal analysis.Conventional estimation methods that use a unique mean individual weight value for nematodes to calculate total biomass may cause deviation of the results.A modified estimation method,named the Subsection Count Method (SCM),was also used to calculate meiofaunal biomass.This entails only a slight increase in workload but generates results of greater accuracy.Results gained using each of these two methods were compared in the present study.The results show that the conventional method generally estimates a meiofaunal biomass.The difference between the two estimation methods was highly significant (P<0.01) for the spring and winter cruises.Furthermore,the estimation method for meiofaunal biomass affected the analysis of horizontal distribution and correlation with environmental factors.These findings highlight the importance of estimation methods for meiofaunal biomass and will hopefully stimulate further investigation and discussion of the topic. 展开更多
关键词 meiofaunal biomass Subsection Count Method estimation method Bohai Bay China
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A review of methods of age estimation based on postmortem computed tomography 认领 引用 被引量：1
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作者 Marta Barszcz Krzysztof Jerzy Wozniak 《Forensic Sciences Research》 CSCD 2025年第1期1-10,共10页
Age at death is one of the key elements of the“biological profile"prepared when analysing unidentified human remains.Biological age is determined according to physiological indicators and developmental stage,whi... Age at death is one of the key elements of the“biological profile"prepared when analysing unidentified human remains.Biological age is determined according to physiological indicators and developmental stage,which can be determined by bone assessment.It is worth remembering that the researcher must interpret each case individually and in accordance with the current state of knowledge.One of the most developed tools for analysing human remains is postmortem computed tomography.This allows for the visualization not only of bones without maceration but also of the entire body under various altered states,including corpses in advanced stages of decomposition and burnt bodies.The aim of this review is to present the current methods for age estimation based on postmortem computed tomography evaluation,comparing the results presented in 18 research projects published between 2013 and 2023 on foetuses,children,and adults from contemporary populations.Recent literature includes assessment of bones and characteristics such as skulls,teeth,vertebrae,pelvises,and long bones to estimate age at death.We cover the methods used in this recent literature,including machine learning,and discuss the advantages and disadvantages of them. 展开更多
关键词 age estimation postmortem computed tomography forensic imaging
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Singularity of Some Software Reliability Models and Parameter Estimation Method 认领 引用 被引量：1
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作者 XU Ren-zuo ZHOU Rui YANG Xiao-qing 《Wuhan University Journal of Natural Sciences》 EI CAS 2000年第1期35-40,共6页
According to the principle, “The failure data is the basis of software reliability analysis”, we built a software reliability expert system (SRES) by adopting the artificial intelligence technology. By reasoning out... According to the principle, “The failure data is the basis of software reliability analysis”, we built a software reliability expert system (SRES) by adopting the artificial intelligence technology. By reasoning out the conclusion from the fitting results of failure data of a software project, the SRES can recommend users “the most suitable model” as a software reliability measurement model. We believe that the SRES can overcome the inconsistency in applications of software reliability models well. We report investigation results of singularity and parameter estimation methods of experimental models in SRES. 展开更多
关键词 software reliability measurement models software reliability expert system singularity parameter estimation method path following method maximum likelihood ML-fitting algorithm
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Direct and indirect methods for uniaxial compressive strength estimation in various geo-environments:A review 认领 引用 被引量：1
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作者 Md Shayan Sabri Amit Kumar Verma T.N.Singh 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2025年第12期8241-8275,共35页
Uniaxial compressive strength(UCS)is a significant mechanical measure in rock engineering,key for classifying rock masses,conducting stability assessments,and guiding design processes.Over the past five decades,numero... Uniaxial compressive strength(UCS)is a significant mechanical measure in rock engineering,key for classifying rock masses,conducting stability assessments,and guiding design processes.Over the past five decades,numerous techniques and devices have emerged for UCS measurement.This paper presents a comprehensive literature review of existing methodologies and advancements in UCS testing,examining the theoretical foundations,testing equipment,data processing techniques,and criteria for selecting appropriate UCS testing methods.Additionally,the study highlights a shift toward automated,precise,and computational approaches with multiple inputs(i.e.multiple regression,machine learning,ML)for UCS prediction.Approximately 221 articles published by various researchers between 2000 and 2024 related to ML were reviewed,focusing on the application of ML models,including artificial neural networks(ANNs),adaptive-network-based fuzzy inference system(ANFIS),random forest(RF),support vector machine(SVM),and extreme gradient boosting(XGBoost),in UCS prediction.The review also observed the growing use of hybrid models integrating ML with optimization techniques,significantly improving UCS estimation.Numerous empirical correlations,both direct and indirect,have been established in the past several years based on the physical properties of rocks.However,utilizing these proposed equations to reliably estimate UCS remains challenging due to the variability in lithology,rock origin,and other factors.This study systematically presents the established correlation expressions,considering their lithology,the number of samples used to establish the expressions,the coefficient of determination(R2),and the locations.This allows geologists and engineers to easily apply these established expressions in situations where direct estimation is not possible,enabling them to approximate UCS results. 展开更多
关键词 Uniaxial compressive strength(UCS) Indirect methods Empirical correlations Machine learning(ML)
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Photometry-free sky area visibility estimation method for All-sky Camera 认领 引用 被引量：1
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作者 Haiwen Xie Hui Zhi +4 位作者 Zhe Kang Shiyu Deng Bingli Niu Lei Wang Xiaojun Jiang 《Astronomical Techniques and Instruments》 CSCD 2025年第1期52-64,共13页
Observatories typically deploy all-sky cameras for monitoring cloud cover and weather conditions.However,many of these cameras lack scientific-grade sensors,r.esulting in limited photometric precision,which makes calc... Observatories typically deploy all-sky cameras for monitoring cloud cover and weather conditions.However,many of these cameras lack scientific-grade sensors,r.esulting in limited photometric precision,which makes calculating the sky area visibility distribution via extinction measurement challenging.To address this issue,we propose the Photometry-Free Sky Area Visibility Estimation(PFSAVE)method.This method uses the standard magnitude of the faintest star observed within a given sky area to estimate visibility.By employing a pertransformation refitting optimization strategy,we achieve a high-precision coordinate transformation model with an accuracy of 0.42 pixels.Using the results of HEALPix segmentation is also introduced to achieve high spatial resolution.Comprehensive analysis based on real allsky images demonstrates that our method exhibits higher accuracy than the extinction-based method.Our method supports both manual and robotic dynamic scheduling,especially under partially cloudy conditions. 展开更多
关键词 All-sky cameras Astronomy image processing Ground-based astronomy Calibration Computational methods Observational astronomy
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Online Estimation Method of Train Wheel-Rail Adhesion Coefficient Based on Parameter Estimation 认领 引用
20
作者 Yi Zhang Wenliang Zhu +2 位作者 Hanbin Wang Chun Tian Jiajun Zhou 《Computer Modeling in Engineering & Sciences》 SCIE EI 2025年第9期2873-2891,共19页
Aiming to address the challenge of directly measuring the real-time adhesion coefficient between wheels and rails,this paper proposes an online estimation algorithm for the adhesion coefficient based on parameter esti... Aiming to address the challenge of directly measuring the real-time adhesion coefficient between wheels and rails,this paper proposes an online estimation algorithm for the adhesion coefficient based on parameter estimation.Firstly,a force analysis of the single-wheel pair model of the train is conducted to derive the calculation relationship for the wheel-rail adhesion coefficient in train dynamics.Then,an estimator based on parameter estimation is designed,and its stability is verified.This estimator is combined with the wheelset force analysis to estimate the wheel-rail adhesion coefficient.Finally,the approach is validated through joint simulations on the MATLAB/Simulink and AMESim platforms,as well as a hardware-in-the-loop semi-physical simulation experimental platform that accounts for system delay and noise conditions.The results indicate that the proposed algorithm effectively tracks changes in the adhesion coefficient during train braking,including the decrease in adhesion when the train brakes and slides,and the overall increase as the train speed decreases.The effectiveness of the algorithm was verified by setting different test conditions.The results show that the estimation algorithm can accurately estimate the adhesion coefficient,and through error analysis,it is found that the error between the estimated value of the adhesion coefficient and the theoretical value of the adhesion coefficient is within 5%.The adhesion coefficient obtained through the online estimation method based on the parameter estimation proposed in this paper demonstrates strong followability in both simulation and practical applications. 展开更多
关键词 Hardware-in-the-loop simulation online parameter estimation rail vehicle wheel-rail adhesion
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