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Dynamic Location Method for Shallow Ocean Bottom Nodes Using the levenberg-marquart algorithm

Journal of Ocean University of China 2024年第4期23卷 953-960页

作者： TONG Siyou LI Junjie XU Xiugang FANG Yunfen WANG Zhongcheng Key Laboratory of Submarine Geosciences and Prospecting Techniques MOEOcean University of ChinaQingdao 266100China Laboratory for Marine Mineral Resources Qingdao Marine Science and Technology CenterQingdao 266237China R&D Center of BGP CNPCZhuozhou 072751China Insitute of Shengli Oilfield SINOPECDongying 257022China

Ocean bottom node(OBN)data acquisition is the main development direction of marine seismic exploration;it is widely promoted,especially in shallow sea ***,the OBN receivers may move several times because they are easily affected by tides,currents,and other factors in the shallow sea environment during long-term *** uncorrected,then the imaging quality of subsequent processing will be *** conventional secondary positioning does not consider the case of multiple movements of the receivers,and the accuracy of secondary positioning is *** first arrival wave of OBN seismic data in shallow ocean mainly comprises refracted *** this study,a nonlinear model is established in accordance with the propagation mechanism of a refracted wave and its relationship with the time interval curve to realize the accurate location of multiple receiver *** addition,the levenberg-marquart algorithm is used to reduce the influence of the first arrival pickup error and to automatically detect the receiver movements,identifying the accurate dynamic relocation of the *** simulation and field data show that the proposed method can realize the dynamic location of multiple receiver movements,thereby improving the accuracy of seismic imaging and achieving high practical value.

关键词： OBN dynamic location method levenberg-marquart algorithm seismic exploration of shallow sea

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Sky-ground wave signal separation in enhanced Loran based on levenberg-marquart algorithm

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IET RADAR SONAR AND NAVIGATION 2022年第1期16卷 1-8页

作者： Zhao, Zhenzhu Liu, Jiangfan Zhang, Jinsheng Xi, Xiaoli Xian Univ Technol Dept Elect Engn 5 South Jinhua Rd Xian 710048 Peoples R China

This study proposes a high-precision algorithm used in enhanced Loran sky-ground wave separation based on the levenberg-marquart algorithm. The simulation results show that, compared with the existing algorithms, the algorithm proposed in this study has higher accuracy, especially in the case of a low signal-to-noise ratio. Furthermore, when the skywave of enhanced Loran has at least a 35 mu s time delay compared with the groundwave, the performance of the algorithm is significantly better than that of other algorithms. Analysis of an actual signal showed that the average correlation coefficient was greater than 99% and that the signal was successfully separated.

关键词： electromagnetic wave propagation enhanced loran signal ionospheric electromagnetic wave propagation levenberg-marquart algorithm sky-ground wave separation signal processing

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Inversion of distributed temperature measurements to interpret the flow profile for a multistage fractured horizontal well in low-permeability gas reservoir

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APPLIED MATHEMATICAL MODELLING 2020年第Part1期77卷 360-377页

作者： Luo, Hongwen Li, Haitao Lu, Yu Li, Ying Guo, Zhenhua Southwest Petr Univ State Key Lab Oil & Gas Reservoir Geol & Exploita Chengdu 610500 Sichuan Peoples R China

Distributed temperature sensors (DT%) are gradually being used to monitor downhole conditions for multistage fractured horizontal wells (MFHWs) during production. However, significant challenges exist with respect to translating the downhole DTS data to flow profiles of MFHWs, especially for low-permeability gas reservoirs (LPGRs). This study aims to interpret the flow profiles for an MFHW in LPGR through the inversion of downhole distributed temperature measurements. Firstly, a comprehensive inversion procedure combined with forward and inversion models is developed. The forward temperature prediction model is used to simulate the temperature distributions of an MFHW in each inversion iteration. Based on the levenberg-marquart (L-M) algorithm, an inversion model is proposed to decrease the differences between the simulated temperature data and the observed temperature data. Subsequently, a sensitivity study using an orthogonal design table L-18 (3(7)) is performed to determine the inversion parameters (fracture half-length and reservoir permeability). Then, an original case demonstrates the direct translation of the observed temperature to the flow profile. Finally, two more cases are presented to illustrate how to interpret the flow profiles based on the inversion results of the two aforementioned inversion parameters respectively. The satisfactory inversion results validate the accuracy and feasibility of the proposed inversion approach to predict flow profiles or diagnose fracture parameters from the DTS data of an MFHW in LPGR theoretically. (C) 2019 Elsevier Inc. All rights reserved.

关键词： Inversion of distributed temperature sensor data levenberg-marquart algorithm Flow profiles Multistage fractured horizontal well Orthogonal experiment design

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Biosorption of chromium (VI) from aqueous solutions and ANN modelling

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2017年第23期24卷 18817-18835页

作者： Nag, Soma Mondal, Abhijit Bar, Nirjhar Das, Sudip Kumar Natl Inst Technol Agartala Agartala India Univ Calcutta Dept Chem Engn Kolkata W Bengal India

The use of sustainable, green and biodegradable natural wastes for Cr(VI) detoxification from the contaminated wastewater is considered as a challenging issue. The present research is aimed to assess the effectiveness of seven different natural biomaterials, such as jackfruit leaf, mango leaf, onion peel, garlic peel, bamboo leaf, acid treated rubber leaf and coconut shell powder, for Cr(VI) eradication from aqueous solution by biosorption process. Characterizations were conducted using SEM, BET and FTIR spectroscopy. The effects of operating parameters, viz., pH, initial Cr(VI) ion concentration, adsorbent dosages, contact time and temperature on metal removal efficiency, were studied. The biosorption mechanism was described by the pseudo-second-order model and Langmuir isotherm model. The biosorption process was exothermic, spontaneous and chemical (except garlic peel) in nature. The sequence of adsorption capacity was mango leaf > jackfruit leaf > acid treated rubber leaf > onion peel > bamboo leaf > garlic peel > coconut shell with maximum Langmuir adsorption capacity of 35.7 mg g(-1) for mango leaf. The treated effluent can be reused. Desorption study suggested effective reuse of the adsorbents up to three cycles, and safe disposal method of the used adsorbents suggested biodegradability and sustainability of the process by reapplication of the spent adsorbent and ultimately leading towards zero wastages. The performances of the adsorbents were verified with wastewater from electroplating industry. The scale-up study reported for industrial applications. ANN modelling using multilayer perception with gradient descent (GD) and levenberg-marquart (LM) algorithm had been successfully used for prediction of Cr(VI) removal efficiency. The study explores the undiscovered potential of the natural waste materials for sustainable existence of small and medium sector industries, especially in the third world countries by protecting the environment by eco-innovation.

关键词： Detoxification Adsorption Chromium( VI) Isotherm ANN Gradient descent levenberg-marquart algorithm

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Analysis of the method for ventilation heterogeneity assessment using the Otis model and forced oscillations

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COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2015年第3期122卷 330-340页

作者： Glapinski, Jaroslaw Mroczka, Janusz Polak, Adam G. Wroclaw Univ Technol Chair Elect & Photon Metrol PL-50370 Wroclaw Poland

Increased heterogeneity of the lung disturbs pulmonary gas exchange. During bronchoconstriction, inflammation of lung parenchyma or acute respiratory distress syndrome, inhomogeneous lung ventilation can become bimodal and increase the risk of ventilator-induced lung injury during mechanical ventilation. A simple index sensitive to ventilation heterogeneity would be very useful in clinical practice. In the case of bimodal ventilation, the index (H) can be defined as the ratio between the longer and shorter time constant characterising regions of contrary mechanical properties. These time constants can be derived from the Otis model fitted to input impedance (Z(in)) measured using forced oscillations. In this paper we systematically investigated properties of the aforementioned approach. The research included both numerical simulations and real experiments with a dual-lung simulator. Firstly, a computational model mimicking the physical simulator was derived and then used as a forward model to generate synthetic flow and pressure signals. These data were used to calculate the input impedance and then the Otis inverse model was fitted to Z, by means of the levenberg-Marquardt (LM) algorithm. Finally, the obtained estimates of model parameters were used to compute H. The analysis of the above procedure was performed in the frame of Monte Carlo simulations. For each selected value of H, forward simulations with randomly chosen lung parameters were repeated 1000 times. Resulting signals were superimposed by additive Gaussian noise. The estimated values of H properly indicated the increasing level of simulated inhomogeneity, however with underestimation and variation increasing with H. The main factor responsible for the growing estimation bias was the fixed starting vector required by the LM algorithm. Introduction of a correction formula perfectly reduced this systematic error. The experimental results with the dual-lung simulator confirmed potential of the proposed pro

关键词： Ventilation heterogeneity Otis model Forced oscillations levenberg-marquart algorithm Monte Carlo simulations Mechanical lung simulator

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Identification of multiple-input single-output Hammerstein models using Bezier curves and Bernstein polynomials

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APPLIED MATHEMATICAL MODELLING 2011年第4期35卷 1969-1982页

作者： Ahmadi, Mohamadreza Mojallali, Hamed Univ Guilan Fac Engn Dept Elect Engn Rasht Iran

This paper considers the implementation of Bezier-Bernstein polynomials and the levenberg-marquart algorithm for identifying multiple-input single-output (MISO) Hammerstein models consisting of nonlinear static functions followed by a linear dynamical subsystem. The nonlinear static functions are approximated by the means of Bezier curves and Bernstein basis functions. The identification method is based on a hybrid scheme including the inverse de Casteljau algorithm, the least squares method, and the levenberg-marquart (LM) algorithm. Furthermore, results based on the proposed scheme are given which demonstrate substantial identification performance. (C) 2010 Elsevier Inc. All rights reserved.

关键词： System identification Hammerstein model Bezier-Bernstein polynomial functions levenberg-marquart algorithm

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Study on Web Classification Mining Method Based on Fuzzy Neural Network

Study on Web Classification Mining Method Based on Fuzzy Neu...

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IEEE International Conference on Automation and Logistics

作者： Tian, Jingwen Gao, Meijuan Sun, Yang Beijing Union Univ Coll Automat Beijing Peoples R China

ISBN: (纸本)9781424447947

With the development and widely used of Internet and information technology, the web has become one of the most important means to obtain information for people. According to the web document classification and the theory of artificial neural network, a web classification mining method based on fuzzy neural network (FNN) is presented in this paper. We construct the structure of fuzzy neural network that used for web text information classification, and adopt the levenberg-marquart optimizing algorithm to train fuzzy neural network, thereby enhancing the convergence rate and the classification accuracy. The structure of web classification mining system based on fuzzy neural network is given. With the ability of strong self-learning and nonlinear function approach and pattern classification of fuzzy neural network, the classification mining method can truly classify the web text information. The actual classification results show that this method is feasible and effective.

关键词： Web mining classification fuzzy neural network levenberg-marquart algorithm

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Applications of improved BP network model and grey model to predict groundwater regime in spring catchment

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Liaoning Gongcheng Jishu Daxue Xuebao (Ziran Kexue Ban)/Journal of Liaoning Technical University (Natural Science Edition) 2007年第SUPPL. 1期26卷 277-279页

作者： Liu, De-Dong Yu, Zhong-Bo Hao, Zhen-Chun Wang, Shu-Qian Zhu, Chang-Jun Ju, Qin State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering Hohai University Nanjing 210098 China Department of Geoscience University of Nevada Las Vevada 89154 United States Resource College Hebei University of Engineering Handan 056038 China

Spring discharge reflects the groundwater regime. In order to find better method for prediction, management and evaluation of groundwater, the improved BP artificial network model-LMBP network and the GM(1, 1) model of grey theory are applied to forecast the springs discharge. The results show that the two models are all able to model the interannual spewing tendency of springs well. And the performance of the LMBP network is better than that of GM(1, 1) prediction model. LMBP network reflects the fluctuating influencing-f actor with large amplitude and has advantage over GM(1, 1) model, it is suggested that the GM(1, 1)model should be improved to be applied to time-series analysis with large amplitude.

关键词： BP neural network Dynamic variation of groundwater GM(1, 1) model levenberg-marquart algorithm Spring discharge

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Rough neural network of variable precision

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NEURAL PROCESSING LETTERS 2004年第1期19卷 73-87页

作者： Liu, HJ Tuo, HY Liu, YC Shanghai Jiao Tong Univ Inst Image Proc & Pattern Recognit Shanghai 200030 Peoples R China

In this paper, a new method is described to construct rough neural networks. On the base of rough set model, we present a method to develop rough neural network of variable precision and train it using levenberg-marquart algorithm. The method is particularly attractive because it combines the advantages of both rough logic networks and neural networks. In our system, weak generalization in rough sets theory and complexity in neural network are avoided while anti-jamming performance is highly improved and the network structure is also simplified. In experiments, the network is applied to classification of remote sensing images. The results show that our method is more effective and successful than application of rough sets and neural network separately.

关键词： levenberg-marquart algorithm neural network rough sets variable precision

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