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An adjoint data assimilation approach for estimating parameters in a three-dimensional ecosystem model

ECOLOGICAL modelLING 2005年第2期186卷 234-249页

作者： Zhao, L Wei, H Xu, YF Feng, SZ Ocean Univ China Inst Phys Oceanog Qingdao 266003 Peoples R China Chinese Acad Sci Inst Atmospher Phys State Key Lab Atmospher Boundary Layer Phys & Atm Beijing 100029 Peoples R China

In this paper an ecosystem model, including phytoplankton, zooplankton, nitrate, ammonium, phosphate and detritus, is described. The model is driven by physical fields derived from a three-dimensional physical transport model. Simulation includes nitrate input from a river. Simulated results are then sampled and the sampled data are used in sequential numerical experiments to assess the ability of using an adjoint data assimilation approach for estimating the poorly known parameters of the ecosystem model, such as growth and death rate, half-saturation constant of nutrients, etc. Data with different spatial and temporal resolution over I week are assimilated into the ecosystem model. Assimilation of data at 30 grid stations with a sampling interval of 6 h is proved to be adequate for recovering all the parameters of the ecosystem model. Both the spatial and temporal resolution of the data are mutually complementary in the assimilative model. Thus, improvement of either of them can result in improvement of model parameter recoveries. The assimilation of phytoplankton data is essential to recover the model parameters. Phytoplankton is the core of the food web and without the information on phytoplankton, the structure of the ecosystem cannot be constructed correctly. The adjoint method can work well with the noisy data. In the twin experiments with noisy data, the parameters can be recovered but the error is increased. The results of the model and parameter recovery are sensitive to the initial conditions of state variables, so the determination of the initial condition is as important as that of the model parameter. The spatial and temporal resolution and the data type of the observations in Analysis and modelling Research of the Ecosystem in the Bohai Sea (AMREB) are suitable for the recovery of the model parameters used in this study. (c) 2005 Elsevier B.V. All rights reserved.

关键词： adjoint method data assimilation ecosystem model model parameters

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Prior Distributions of Material parameters for Bayesian Calibration of Growth and Remodeling Computational model of Abdominal Aortic Wall

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JOURNAL OF BIOMECHANICAL ENGINEERING-TRANSACTIONS OF THE ASME 2015年第10期137卷 101001页

作者： Seyedsalehi, Sajjad Zhang, Liangliang Choi, Jongeun Baek, Seungik Michigan State Univ Dept Mech Engn E Lansing MI 48824 USA Michigan State Univ Dept Stat & Probabil E Lansing MI 48824 USA Michigan State Univ Dept Mech Engn Dept Elect & Comp Engn E Lansing MI 48824 USA

For the accurate prediction of the vascular disease progression, there is a crucial need for developing a systematic tool aimed toward patient-specific modeling. Considering the interpatient variations, a prior distribution of model parameters has a strong influence on computational results for arterial mechanics. One crucial step toward patient-specific computational modeling is to identify parameters of prior distributions that reflect existing knowledge. In this paper, we present a new systematic method to estimate the prior distribution for the parameters of a constrained mixture model using previous biaxial tests of healthy abdominal aortas (AAs). We investigate the correlation between the estimated parameters for each constituent and the patient's age and gender;however, the results indicate that the parameters are correlated with age only. The parameters are classified into two groups: Group-I in which the parameters c(e), c(k1), c(k2), c(m2), G(h)(c), and phi(e) are correlated with age, and Group-II in which the parameters c(m1), G(h)(m), G(1)(e), G(2)(e), and alpha are not correlated with age. For the parameters in Group-I, we used regression associated with age via linear or inverse relations, in which their prior distributions provide conditional distributions with confidence intervals. For Group-II, the parameter estimated values were subjected to multiple transformations and chosen if the transformed data had a better fit to the normal distribution than the original. This information improves the prior distribution of a subject- specific model by specifying parameters that are correlated with age and their transformed distributions. Therefore, this study is a necessary first step in our group's approach toward a Bayesian calibration of an aortic model. The results from this study will be used as the prior information necessary for the initialization of Bayesian calibration of a computational model for future applications.

关键词： abdominal aortic aneurysm model parameters G&R model correlation age

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Training large-scale language models with limited GPU memory:a survey

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Frontiers of Information Technology & Electronic Engineering 2025年第3期26卷 309-331页

作者： Yu TANG Linbo QIAO Lujia YIN Peng LIANG Ao SHEN Zhilin YANG Lizhi ZHANG Dongsheng LI National Key Laboratory of Parallel and Distributed Computing College of ComputerNational University of Defense TechnologyChangsha 410073China

Large-scale models have gained significant attention in a wide range of fields,such as computer vision and natural language processing,due to their effectiveness across various ***,a notable hurdle in training these large-scale models is the limited memory capacity of graphics processing units(GPUs).In this paper,we present a comprehensive survey focused on training large-scale models with limited GPU *** exploration commences by scrutinizing the factors that contribute to the consumption of GPU memory during the training process,namely model parameters,model states,and model *** this analysis,we present an in-depth overview of the relevant research work that addresses these aspects ***,the paper concludes by presenting an outlook on the future of memory optimization in training large-scale language models,emphasizing the necessity for continued research and innovation in this *** survey serves as a valuable resource for researchers and practitioners keen on comprehending the challenges and advancements in training large-scale language models with limited GPU memory.

关键词： Training techniques Memory optimization model parameters model states model activations

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DETERMINATION OF THE parameters OF LIMIT STATE model FOR STRUCTURAL MATERIALS UNDER ASYMMETRIC HIGH-CYCLE LOADING

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STRENGTH OF MATERIALS 2012年第1期44卷 33-39页

作者： Regul'skii, M. N. Pogrebnyak, A. D. Pelykh, V. N. Natl Acad Sci Ukraine Timoschenko Inst Mech Kiev Ukraine

The paper considers a procedure for the determination of the parameters of a limit state model for structural materials using a transcendental power function. The model is used to construct limiting stress amplitude diagrams for asymmetric high-cycle loading. The procedure has been tested by comparing the values of limit state model parameters obtained as a result of the basic experiment in pulsating loading cycle with the values calculated by the method of minimization of the sum-of-squares functional of deviations of experimental diagrams from calculated ones.

关键词： fatigue resistance asymmetric high-cycle loading limit state model model parameters structural materials

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CLASSIFYING KIDNEY DISEASE IN A VERVET model USING SPATIALLY ENCODED CONTRAST-ENHANCED ULTRASOUND PERFUSION parameters

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ULTRASOUND IN MEDICINE AND BIOLOGY 2023年第3期49卷 761-772页

作者： Alhmoud, Issa W. Walmer, Rachel W. Kavanagh, Kylie Chang, Emily H. Johnson, Kennita A. Bikdash, Marwan North Carolina A&T State Univ Computat Data Sci & Engn Greensboro NC USA North Carolina State Univ Joint Dept Biomed Engn Raleigh NC USA Univ North Carolina Chapel Hill Raleigh NC USA Wake Forest Univ Dept Pathol Sch Med Winston Salem NC USA Univ Tasmania Coll Hlth & Med Hobart Tas Australia Univ North Carolina Chapel Hill Sch Med Chapel Hill NC USA 116 Manning Dr 10202A Mary Ellen Jones Bldg CB 7 Chapel Hill NC 27599 USA

Early stages of diabetic kidney disease (DKD) are difficult to diagnose in patients with type 2 diabetes. This work was aimed at identifying contrast-enhanced ultrasound (CEUS) perfusion parameters, a microcirculatory biomarker indicative of early DKD progression. CEUS kidney nashreplenishment data were acquired in control, insulin resistant and diabetic vervet monkeys (N = 16). By use of a mono-exponential model, time-inten-sity curve parameters related to blood volume (A), velocity (beta) and now rate (perfusion index [PI]) were extracted from 10 concentric kidney layers to study spatial perfusion patterns that could serve as strong indicators of dis-ease. Mean squared error (MSE) was used to assess model performance. Features calculated from the perfusion parameters were inputs for the linear regression models to determine which features could distinguish between cohorts. The mono-exponential model performed well, with average MSEs (+/- standard deviation) of 0.0254 (+/- 0.0210), 0.0321 (+/- 0.0242) and 0.0287 (+/- 0.0130) for the control, insulin resistant and diabetic cohorts, respectively. Perfusion index features, with blood pressure, were the best classifiers between cohorts (p < 0.05). CEUS has the potential to detect early microvascular changes, providing insight into disease-related structural changes in the kidney. The sensitivity of this technique should be explored further by assessing various stages of DKD. (E-mail: kennita@***) (c) 2022 The Author(s). Published by Elsevier Inc. on behalf of World Federation for Ultrasound in Medicine & Biology. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Contrast ultrasound Perfusion imaging Diabetic kidney disease Segmentation model parameters Regression analysis

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Response of the parameters of excess infiltration and excess storage model to land use cover change

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JOURNAL OF HYDROLOGY AND HYDROMECHANICS 2020年第2期68卷 99-110页

作者： Wen, Yuexiu Hu, Caihong Zhang, Guodong Jian, Shengqi Zhengzhou Univ Coll Water Conservancy & Environm Sci Rd 100 Zhengzhou Peoples R China Henan Yellow River Hydrol Survey & Design Inst Chengdong Rd 100 Zhengzhou Peoples R China

The Loess Plateau is the main source of water in Yellow River, China. After 1980s, the Yellow river water presented a significant reduction, what caused the decrease of the Yellow river discharge had been debated in academic circles. We proceeded with runoff generation mechanisms to explain this phenomenon. We built saturation excess runoff and infiltration excess runoff generation mechanisms for rainfall-runoff simulation in Jingle sub-basin of Fen River basin on the Loess Plateau, to reveal the influence of land use change on flood processes and studied the changes of model parameters under different underlying conditions. The results showed that the runoff generation mechanism was mainly infiltration-excess overland flow, but the flood events of saturation-excess overland flow had an increasing trend because of land use cover change (the increase of forestland and grassland areas and the reduction of cultivated land). Some of the model parameters had physical significances,such as water storage capacity (WM), infiltration capacity (f), evapotranspiration (CKE), soil permeability coefficient (k) and index of storage capacity distribution curve (n) showed increasing trends, and index of infiltration capacity distribution curve (m) showed a decreasing trend. The above results proved the changes of runoff generation mechanism from the perspective of model parameters in Jingle sub-basin, which can provide a new perspective for understanding the discharge reduction in the Yellow River basin.

关键词： Land use Saturation excess and infiltration excess model model parameters Fen River

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Estimation of the parameters of the discrete model of a steel-concrete composite beam

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ARCHIVES OF CIVIL AND MECHANICAL ENGINEERING 2013年第2期13卷 209-219页

作者： Wroblewski, T. Berczynski, S. Abramowicz, M. West Pomeranian Univ Technol Dept Mech Engn & Mechatron PL-70310 Szczecin Poland West Pomeranian Univ Technol Dept Civil Engn & Architecture PL-70311 Szczecin Poland

This paper presents estimations of mathematical models' parameters regarding steel-concrete composite beams' natural vibrations. The model was created using Rigid Finite Element (RFE) Method. parameters' estimation was done based on the results of experimental research, conducted on actual composite beams. Estimated parameters include: shearing and axial stiffness of connecting elements, and substitute longitudinal modulus of elasticity of the reinforced concrete slab, which takes into account longitudinal reinforcement. Employing the appropriate criteria during the process of estimation of the parameters of the steel-concrete composite beam models has a great impact on getting precise results. The estimation criteria were selected in order to achieve consistency of the natural vibration frequencies, along with vibration modes, measured during experimental and calculated based on the mathematical model. The models and all the calculations were made using the MATLAB programming environment. (C) 2013 Politechnika Wroclawska. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

关键词： Rigid finite element (RFE) model Steel-concrete composite beams Criteria of the estimation model parameters Vibrations

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modeling and Parameter Analysis of Basic Single Channel Neuron Mass model for SSVEP

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SENSORS 2025年第6期25卷

作者： Gao, Depeng Wang, Yujuan Fu, Peirong Qiu, Jianlin Li, Hongqi Nontong Inst Technol Sch Yonyou Digital & Intelligence Nantong 226000 Peoples R China Northwestern Polytech Univ Sch Software Xian 710000 Peoples R China

While steady-state visual evoked potentials (SSVEPs) are widely used in brain-computer interfaces (BCIs) due to their robustness to rhythmic visual stimuli, their generation mechanisms remain poorly understood. Challenges such as experimental complexity, inter-subject variability, and limited physiological interpretability hinder the development of efficient BCI systems. This study employed a single-channel neural mass model (NMM) of V1 cortical dynamics to investigate the biophysical underpinnings of SSVEP generation. By systematically varying synaptic gain, time constants, and external input parameters, we simulated delta/alpha/gamma band oscillations and analyzed their generation principles. The model demonstrates that synaptic gain controls oscillation amplitude and harmonic content, and time constants determine signal decay kinetics and frequency precision, while input variance modulates harmonic stability. Our results reveal how V1 circuitry generates frequency-locked SSVEP responses through excitatory-inhibitory interactions and dynamic filtering mechanisms. This computational framework successfully reproduces fundamental SSVEP characteristics without requiring multi-subject experimental data, offering new insights into the physiological basis of SSVEP-based brain-computer interfaces.

关键词： steady-state visually evoked potential neural mass model model parameters parameter analysis motion control

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Effects of Internal Erosion on parameters of Subloading Cam-Clay model

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GEOTECHNICAL AND GEOLOGICAL ENGINEERING 2020年第2期38卷 1323-1335页

作者： Gang, Wang Horikoshi, Kazuki Takahashi, Akihiro Tokyo Inst Technol Dept Civil & Environm Engn Meguro Ku 2-12-1-M1-3 Oh Okayama Tokyo 1528552 Japan

Internal erosion is widely detected in both natural deposits and earthen structures and potentially causes severe disasters. Suffusion is one of the modes of internal erosion in which fine particles in the soil are washed out along with water flow through pores formed by coarse particles. Mechanical consequences of internal erosion, specifically, suffusion, are not well investigated in term of constitutive modeling. Also, most of the present constitutive models concerning suffusion are validated by DEM simulations, not by actual soil response observed in soil tests. In this paper, triaxial seepage tests followed by drained compression on soil with 35% initial fines content under 50 kPa, 100 kPa and 200 kPa mean stresses are studied to investigate the applicability of the existing soil model to internally eroded soils. The subloading Cam-clay model is used to simulate the mechanical behavior of eroded soils. After confirming that the model can capture key features of uneroded specimens, the evolution of model parameters with erosion is examined by back analysis of the eroded specimens. From the simulation on the eroded specimens, evolutions of the slope of normal compression line and initial stress ratio with erosion are quantified. The changes of model parameters with erosion provide a useful reference for investigating the mechanical behaviour of granular materials subjected to suffusion.

关键词： Internal erosion Suffusion Granular materials model parameters Subloading Cam-clay model

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Optimization of the Energy Extraction Process From Capacitive Deionization Cells

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2025年

作者： Busto, Maria G. Prieto, Miguel J. Martin-Ramos, Juan A. Martinez, Juan A. Pernia, Alberto M. Univ Oviedo Dept Elect Elect Commun & Syst Engn Gijon 33203 Spain

Capacitive deionization cells, already present in different industrial applications, can also be used to generate electrical energy by alternating salt and fresh water flows (CapMix cells). Unfortunately, the performance inherent to these cells gives rise to large losses when extracting the energy harvested. This article provides contributions to the appropriate characterization of CapMix cells and to the optimization of the energy-extraction process. The optimization analysis carried out concludes that the best strategy consists of extracting the energy by discharging the cell with a constant current to minimize cycle times. This determines the operation conditions of the power converter that will be eventually used for that task. A test bench has been developed that allows the theoretical analysis presented to be experimentally validated.

关键词： Carbon Electrodes Resistance Ions Electric potential Optimization Titanium Supercapacitors Salinity (geophysical) Renewable energy sources Blue energy CapMix cell model parameters optimized energy harvesting remote sensor supply

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