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Slip distribution inversion of seismic sub-fault dip iteration using gradient based optimizer algorithm

Geodesy and Geodynamics 2024年第2期15卷 114-121页

作者： Leyang Wang Han Li Ming Pang key laboratory of mine environmental monitoring and improving around poyang lake of Ministry of Natural Resources East China University of TechnologyNanchang 330013China School of Surveying and Geoinformation Engineering East China University of TechnologyNanchang 330013China College of Resources and Environment Shandong Agricultural UniversityTaian 271018China

This paper considers setting different dips for different sub-faults to fit the actual rupture situation based on the fault rupture of the 2013 Lushan M_(S)7.0 earthquake.Meanwhile,combined with the coseismic GNSS data of the Lushan earthquake,the source parameters and sliding distribution of the Lushan earthquake fault are inversed.Firstly,we use the gradient based optimizer(GBO)in nonlinear inversion to obtain the source parameters of this seismic fault.The inversion results indicate that the strike of the fault is 206.52°,the dip is 44.10°,the length is 21.92 km,and the depth is 12.79 km.To refine the sliding distribution of the seismic fault,the seismic fault is divided into 3×3 sub-faults.Then,we fix the central sub-fault dip of 44.10°;the dip of other sub-faults is obtained by iteration.After that,the model is further divided into a fault layer model composed of 23×19 sub fault slices,and using the Matlab fitting function is used to fit the dip of the 23×19 sub faults.Finally,the Lushan seismic fault plane is established as a shovel structure with steep upper and gentle lower,steep south and gentle north.The slip distribution inversion results indicate that the depth of the slip peak is 13 km,the corresponding maximum slip momentum is 0.67 m,the seismic moment is 1.10×10^(19)N·m and the corresponding moment magnitude is MW6.66.The results above are consistent with the research results of seismology.

关键词： Gradient basedoptimizer(GBO) Lushan earthquake Non-planefault model Slid distribution

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The GNSS PWV retrieval using non-observation meteorological parameters based on ERA5 and its relation with precipitation

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Geodesy and Geodynamics 2024年第3期15卷 302-313页

作者： Weifeng Yang Zhiping Chen Kaiyun Lv Pengfei Xia Tieding Lu School of Surveying and Geoinformation Engineering East China University of TechnologyNanchang 330013China key laboratory of mine environmental monitoring and improving around poyang lake of Ministry of Natural Resources East China University of TechnologyNanchang 330013China State key laboratory of Geodesy and Earth's Dynamics Innovation Academy for Precision Measurement Science and TechnologyChinese Academy of SciencesWuhan 430077China Jiangxi Province Engineering Research Center of Surveying Mapping and Geographic InformationNanchang 330025China School of Geodesy and Geomatics Wuhan UniversityWuhan 430079China

The pressure and temperature significantly influence precipitable water vapor(PWV) retrieval. Global Navigation Satellite System(GNSS) PWV retrieval is limited because the GNSS stations lack meteorological sensors. First, this article evaluated the accuracy of pressure and temperature in 68 radiosonde stations in China based on ERA5 Reanalysis data from 2015 to 2019 and compared them with GPT3model. Then, the accuracy of pressure and temperature calculated by ERA5 were estimated in 5 representative IGS stations in China. And the PWV calculated by these meteorological parameters from ERA5(ERA5-PWV) were analyzed. Finally, the relation between ERA5-PWV and precipitation was deeply explored using wavelet coherence analysis in IGS stations. These results indicate that the accuracy of pressure and temperature of ERA5 is better than the GPT3 model. In radiosonde stations, the mean BIAS and MAE of pressure and temperature in ERA5 are-0.41/1.15 hpa and-0.97/2.12 K. And the mean RMSEs are 1.35 hpa and 2.87 K, which improve 74.77% and 40.58% compared with GPT3 model. The errors of pressure and temperature of ERA5 are smaller than the GPT3 model in bjfs, hksl and wuh2, and the accuracy of ERA5-PWV is improved by 18.77% compared with the GPT3 model. In addition, there is a significant positive correlation between ERA5-PWV and precipitation. And precipitation is always associated with the sharp rise of ERA5-PWV, which provides important references for rainfall prediction.

关键词： ERA5 GNSS Precipitable water vapor Precipitation Wavelet coherence analysis

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The improved artificial bee colony algorithm for mixed additive and multiplicative random error model and the bootstrap method for its precision estimation

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Geodesy and Geodynamics 2023年第3期14卷 244-253页

作者： Leyang Wang Shuhao Han Faculty of Geomatics East China University of TechnologyNanchang 330013China key laboratory of mine environmental monitoring and improving around poyang lake Ministry of Natural ResourcesNanchang 330013China

To solve the complex weight matrix derivative problem when using the weighted least squares method to estimate the parameters of the mixed additive and multiplicative random error model(MAM error model),we use an improved artificial bee colony algorithm without derivative and the bootstrap method to estimate the parameters and evaluate the accuracy of MAM error model.The improved artificial bee colony algorithm can update individuals in multiple dimensions and improve the cooperation ability between individuals by constructing a new search equation based on the idea of quasi-affine transformation.The experimental results show that based on the weighted least squares criterion,the algorithm can get the results consistent with the weighted least squares method without multiple formula derivation.The parameter estimation and accuracy evaluation method based on the bootstrap method can get better parameter estimation and more reasonable accuracy information than existing methods,which provides a new idea for the theory of parameter estimation and accuracy evaluation of the MAM error model.

关键词： Mixed additive and multiplicative random error Parameter estimation Accuracy evaluation Artificial bee colony algorithm Bootstrap method

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Improved cat swarm optimization for parameter estimation of mixed additive and multiplicative random error model

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Geodesy and Geodynamics 2023年第4期14卷 385-391页

To estimate the parameters of the mixed additive and multiplicative(MAM)random error model using the weighted least squares iterative algorithm that requires derivation of the complex weight array,we introduce a derivative-free cat swarm optimization for parameter estimation.We embed the Powell method,which uses conjugate direction acceleration and does not need to derive the objective function,into the original cat swarm optimization to accelerate its convergence speed and search accuracy.We use the ordinary least squares,weighted least squares,original cat swarm optimization,particle swarm algorithm and improved cat swarm optimization to estimate the parameters of the straight-line fitting MAM model with lower nonlinearity and the DEM MAM model with higher nonlinearity,respectively.The experimental results show that the improved cat swarm optimization has faster convergence speed,higher search accuracy,and better stability than the original cat swarm optimization and the particle swarm algorithm.At the same time,the improved cat swarm optimization can obtain results consistent with the weighted least squares method based on the objective function only while avoiding multiple complex weight array derivations.The method in this paper provides a new idea for theoretical research on parameter estimation of MAM error models.

关键词： Mixed additive and multiplicative random error model Parameter estimation Least squares Cat swarm optimization Powell method

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A new polar motion prediction method combined with the difference between polar motion series

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Geodesy and Geodynamics 2022年第6期13卷 564-572页

作者： Leyang Wang Wei Miao Fei Wu Faculty of Geomatics East China University of TechnologyNanchang 330013China key laboratory of mine environmental monitoring and improving around poyang lake Ministry of Natural ResourcesNanchang 330013China

After the first Earth Orientation Parameters Prediction Comparison Campaign(1 st EOP PCC),the traditional method using least-squares extrapolation and autoregressive(LS+AR)models was considered as one of the polar motion prediction methods with higher accuracy.The traditional method predicts individual polar motion series separately,which has a single input data and limited improvement in prediction accuracy.To address this problem,this paper proposes a new method for predicting polar motion by combining the difference between polar motion series.The X,Y,and Y-X series were predicted separately using LS+AR models.Then,the new forecast value of X series is obtained by combining the forecast value of Y series with that of Y-X series;the new forecast value of Y series is obtained by combining the forecast value of X series with that of Y-X series.The hindcast experimental comparison results from January 1,2011 to April 4,2021 show that the new method achieves a maximum improvement of 12.95%and 14.96%over the traditional method in the X and Y directions,respectively.The new method has obvious advantages compared with the differential method.This study tests the stability and superiority of the new method and provides a new idea for the research of polar motion prediction.

关键词： Earth rotation parameters Polar motion prediction LS+AR Differences between series Mean absolute error

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GBO algorithm for seismic source parameters inversion

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Geodesy and Geodynamics 2023年第2期14卷 182-190页

作者： Leyang Wang Han Li Faculty of Geomatics East China University of TechnologyNanchang 330013China key laboratory of mine environmental monitoring and improving around poyang lake Ministry of Natural ResourcesNanchang 330013China

The use of geodetic observation data for seismic fault parameters inversion is the research hotspot of geodetic inversion, and it is also the focus of studying the mechanism of earthquake occurrence. Seismic fault parameters inversion has nonlinear characteristics, and the gradient-based optimizer(GBO) has the characteristics of fast convergence speed and falling into local optimum hardly. This paper applies GBO algorithm to simulated earthquakes and real LuShan earthquakes in the nonlinear inversion of the Okada model to obtain the source parameters. The simulated earthquake experiment results show that the algorithm is stable, and the seismic source parameters obtained by GBO are slightly closer to the true value than the multi peak particle swarm optimization(MPSO). In the 2013 LuShan earthquake experiment, the root mean square error between the deformation after forwarding of fault parameters obtained by the introduced GBO algorithm and the surface observation deformation was 3.703 mm, slightly better than 3.708 mm calculated by the MPSO. Moreover, the inversion result of GBO algorithm is better than MPSO algorithm in stability. The above results show that the introduced GBO algorithm has a certain practical application value in seismic fault source parameters inversion.

关键词： Fault source parameters inversion Gradient-based optimizer algorithm Nonlinear Multi-peak particle swarm optimization algorithm GPS data

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Genetic Nelder-Mead neural network algorithm for fault parameter inversion using GPS data

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Geodesy and Geodynamics 2022年第4期13卷 386-398页

作者： Leyang Wang Ranran Xu Fengbin Yu Faculty of Geomatics East China University of TechnologyNanchang 330013China Faculty of Industrial Safety and Occupational Health Jiangsu College of Safety TechnologyXuzhou 221000China key laboratory of mine environmental monitoring and improving around poyang lake Ministry of Natural ResourcesNanchang 330013China BGI Engineering Consultants Ltd. Beijing 100038China

The traditional genetic algorithm(GA)has unstable inversion results and is easy to fall into the local optimum when inverting fault parameters.Therefore,this article considers the combination of GA with other non-linear algorithms in order to improve the inversion precision of GA.This paper proposes a genetic Nelder-Mead neural network algorithm(GNMNNA).This algorithm uses a neural network algorithm(NNA)to optimize the global search ability of GA.At the same time,the simplex algorithm is used to optimize the local search capability of the GA.Through numerical examples,the stability of the inversion algorithm under different strategies is explored.The experimental results show that the proposed GNMNNA has stronger inversion stability and higher precision compared with the existing algorithms.The effectiveness of GNMNNA is verified by the BodrumeKos earthquake and Monte Cristo Range earthquake.The experimental results show that GNMNNA is superior to GA and NNA in both inversion precision and computational stability.Therefore,GNMNNA has greater application potential in complex earthquake environment.

关键词： Fault parameter inversion Genetic algorithm Nelder-Mead simplex algorithm Neural network algorithm

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A new method for coseismic offset detection from GPS coordinate time series

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Geodesy and Geodynamics 2023年第6期14卷 551-558页

作者： Zhiwei Yang Guangyu Xu Tengxu Zhang Mingkai Chen FeiWu Zhiping Chen School of Surveying and Geoinformation Engineering East China University of TechnologyNanchang 330013China key laboratory of mine environmental monitoring and improving around poyang lake of Ministry of Natural Resources East China University of TechnologyNanchang 330013China key laboratory for Digital Land and Resources of Jiangxi Province East China University of TechnologyNanchang 330013China Hubei Luojia laboratory Wuhan 430079China College of Resources and environmental Science and Engineering Hubei University of Science and TechnologyXianning 437100China

Currently,the extraction of coseismic offset signals primarily relies on earthquake catalog data to determine the occurrence time of earthquakes.This is followed by the process of differencing the average GPS coordinate time series data,with a time interval of 3 to 5 days before and after the earthquake.In the face of the huge amount of GPS coordinate time series data today,the conventional approach of relying on earthquake catalog data to assist in obtaining coseismic offset signals has become increasingly burdensome.To address this problem,we propose a new method for automatically detecting coseismic offset signals in GPS coordinate time series without an extra earthquake catalog for reference.Firstly,we pre-process the GPS coordinate time series data for filtering out stations with significant observations missing and detecting and removing outliers.Secondly,we eliminate other signals and errors in the GPS coordinate time series,such as trend and seasonal signals,leaving the coseismic offset signals as the primary signal.The resulting coordinate time series is then modeled using the first-order difference and data stacking method.The modeling method enables automatic detection of the coseismic offset signals in the GPS coordinate time series.The aforementioned method is applied to automatically detect coseismic offset signals using simulated data and the Searles Valley GPS data in California,USA.The results demonstrate the efficacy of our proposed method,successfully detecting coseismic offsets from vast amounts of GPS coordinate time series data.

关键词： GPS Coordinate time series Coseismic offset Signal detection

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Nitrogen-enriched micro-mesoporous carbon derived from polymers organic frameworks for high-performance capacitive deionization

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Journal of environmental Sciences 2022年第1期34卷 282-291页

作者： Jianpei Zhang Xun-an Ning Danping Li Yi Wang Xiaojun Lai Weixuan Ou Guangzhou key laboratory of environmental Catalysis and Pollution Control School of Environment Science and EngineeringInstitute of Environmental Health and Pollution ControlGuangdong University of TechnologyGuangzhou 510006China School of Land Resources and Environment Key Laboratory of Agricultural Resource and Ecology in the Poyang Lake Basin of Jiangxi ProvinceJiangxi Agricultural UniversityNanchang 330045China

Nitrogenization is an effective method for improving the capacitive deionization(CDI)performance of porous carbon materials.In particular,polymer organic frameworks with heteroatom doping,containing an ordered pore structure and excellent electrochemical stability,are ideal precursors for carbon materials for high-performance CDI.In this study,a nitrogen-enriched micro-mesoporous carbon(NMC)electrode was fabricated by carbonizing a Schiff base network-1 at 500,600,and 700℃.Scanning electron microscopy,Fourier transform infrared spectroscopy,X-ray diffraction,N_(2) adsorption-desorption,the contact angle of water,cyclic voltammetry,and electrochemical impedance spectroscopy were used to characterize the morphological structure,wettability,Brunauer–Emmett–Teller surface areas,and electrochemical performance of the NMCs.The results showed that the NMC carbonized at 600℃ achieved the best specific capacitance(152.33 F/g),as well as a high electrosorption capacity(25.53 mg/g)because of its chemical composition(15.57%N)and surface area(312 m^(2)/g).These findings prove that NMC is viable as an electrode material for desalination by high-performance CDI applications.

关键词： Polymers organic frameworks Nitrogen-doped carbon Micro-mesoporous Carbon Capacitive deionization

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Toxicity mechanisms and bioavailability of copper to fish based on an adverse outcome pathway analysis

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Journal of environmental Sciences 2023年第5期127卷 495-507页

作者： Wei Liao Ziwei Zhu Chenglian Feng Zhenfei Yan Yajun Hong Daqing Liu Xiaowei Jin State key laboratory of environmental Criteria and Risk Assessment Chinese Research Academy of Environmental SciencesBeijing 100012China Wetland Research Center Jiangxi Academy of ForestryNanchang 330032China key laboratory of poyang lake Environment and Resource Utilization Ministry of EducationSchool of Environmental and Chemical EngineeringNanchang UniversityNanchang 330031China Jiangxi Irrigation Experiment Central Station Nanchang 330201China China National environmental monitoring Centre Beijing 100012China

Copper(Cu)exists in a variety of forms in different aquatic environments,and affects their bioavailability.In this study we provide a systematic review on toxicity of Cu which focuses on identifying evidence in the mechanisms of Cu toxicity,and apply an adverse outcome pathway(AOP)analysis to identify multiple potential mechanisms and their interactions of Cu toxicity to fish.This analysis process included the mechanisms of behavior toxicant,oxidative toxicant,ion regulation disruption toxicity,as well as endocrine disruption toxicity.It was found that at low levels of Cu exposure,swimming,avoid predators,locating prey and other sensory functions will be impaired,and the organism will suffer from metabolic alkalosis and respiratory acidosis following the inhibition of the carbonic anhydrase active.The main pathway of acute toxicity of Cu to fish is the inhibition of the Na^(+)/K^(+)-ATPase enzyme,and lead to reduced intracellular sodium absorption,as well as Cu-induced increased cell permeability,in turn resulting in increased sodium ion loss,leading to cardiovascular collapse and respiratory insufficiency.The endocrine disruption toxicity of Cu to fish caused growth inhibition and reproductive reduction.In addition,there are several key pathways of Cu toxicity that are affected by hardness(e.g.,Ca^(2+))and intracellular DOC concentrations,including inhibiting Cu-induction,improving branchial gas exchange,altering membrane transport functions,decreasing Na+loss,and increasing Na+uptake.The results of the AOP analysis will provide a robust framework for future directed research on the mechanisms of Cu toxicity.

关键词： Copper Toxic effect Adverse outcome pathway Aquatic environment Risk assessment

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