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Source quantitative identification by Reference-Based Cubic Blind Deconvolution Algorithm

Chinese Journal of Mechanical Engineering 2023年第4期36卷 180-195页

作者： Xin Luo Zhousuo Zhang Teng Gong Yongjie Li State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong UniversityXi’an 710049China

The semi-blind deconvolution algorithm improves the separation accuracy by introducing reference information.However,the separation performance depends largely on the construction of reference signals.To improve the robustness of the semi-blind deconvolution algorithm to the reference signals and the convergence speed,the reference-based cubic blind deconvolution algorithm is proposed in this paper.The proposed algorithm can be combined with the contribution evaluation to provide trustworthy guidance for suppressing satellite micro-vibration.The normalized reference-based cubic contrast function is proposed and the validity of the new contrast function is theoretically proved.By deriving the optimal step size of gradient iteration under the new contrast function,we propose an efficient adaptive step optimization method.Furthermore,the contribution evaluation method based on vector projection is presented to implement the source contribution evaluation.Numerical simulation analysis is carried out to validate the availability and superiority of this method.Further tests given by the simulated satellite experiment and satellite ground experiment also confirm the effectiveness.The signals of control moment gyroscope and flywheel were extracted,respectively,and the contribution evaluation of vibration sources to the sensitive load area was realized.This research proposes a more accurate and robust algorithm for the source separation and provides an effective tool for the quantitative identification of the mechanical vibration sources.

关键词： quantitative identification Reference-based cubic contrast function Semi-blind deconvolution Satellite micro-vibration Adaptive step size

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quantitative identification of crop disease and nitrogen-water stress in winter wheat using continuous wavelet analysis

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International Journal of Agricultural and Biological Engineering 2018年第2期11卷 145-152页

作者： Wenjiang Huang Junjing Lu Huichun Ye Weiping Kong A.Hugh Mortimer Yue Shi State Key Laboratory of Remote Sensing Science Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijing 100094China Key Laboratory of Digital Earth Science Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijing 100094China Institute of Geographical Science Hebei Academy of SciencesShijiazhuang 050021China Hainan Provincial Key Laboratory of Earth Observation Sanya 572029HainanChina Rutherford Appleton Laboratory Harwell Science and Innovations CampusOxfordshire OX110QXUK

It is necessary to quantitatively identify different diseases and nitrogen-water stress for the guidance in spraying specific fungicides and fertilizer applications.The winter wheat diseases,in combination with nitrogen-water stress,are therefore common causes of yield loss in winter wheat in China.Powdery mildew(Blumeria graminis)and stripe rust(Puccinia striiformis f.sp.Tritici)are two of the most prevalent winter wheat diseases in China.This study investigated the potential of continuous wavelet analysis to identify the powdery mildew,stripe rust and nitrogen-water stress using canopy hyperspectral data.The spectral normalization process was applied prior to the analysis.Independent t-tests were used to determine the sensitivity of the spectral bands and vegetation index.In order to reduce the number of wavelet regions,correlation analysis and the independent t-test were used in conjunction to select the features of greatest importance.Based on the selected spectral bands,vegetation indices and wavelet features,the discriminate models were established using Fisher’s linear discrimination analysis(FLDA)and support vector machine(SVM).The results indicated that wavelet features were superior to spectral bands and vegetation indices in classifying different stresses,with overall accuracies of 0.91,0.72,and 0.72 respectively for powdery mildew,stripe rust and nitrogen-water by using FLDA,and 0.79,0.67 and 0.65 respectively by using SVM.FLDA was more suitable for differentiating stresses in winter wheat,with respective accuracies of 78.1%,95.6%and 95.7%for powdery mildew,stripe rust,and nitrogen-water stress.Further analysis was performed whereby the wavelet features were then split into high-scale and low-scale feature subsets for identification.The accuracies of high-scale and low-scale features with an overall accuracy(OA)of 0.61 and 0.73 respectively were lower than those of all wavelet features with an OA of 0.88.The detection of the severity of stripe rust using this method showed an enhanced reliability(R^(2

关键词： winter wheat crop disease powdery mildew stripe rust nitrogen-water stress continuous wavelet analysis quantitative identification

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A new spectral index for the quantitative identification of yellow rust using fungal spore information

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Big Earth Data 2021年第2期5卷 201-216页

作者： Yu Ren Huichun Ye Wenjiang Huang Huiqin Ma Anting Guo Chao Ruan Linyi Liu Binxiang Qian Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesBeijingChina University of Chinese Academy of Sciences BeijingChina Hainan Key Laboratory of Earth Observation Hainan Institute of Aerospace InformationChinese Academy of SciencesSanyaChina

Yellow rust(Puccinia striiformis f.sp.Tritici)is a frequently occurring fungal disease of winter wheat(Triticum aestivum L.).During yellow rust infestation,fungal spores appear on the surface of the leaves as yellow and narrow stripes parallel to the leaf veins.We analyzed the effect of the fungal spores on the spectra of the diseased leaves to find a band sensitive to yellow rust and established a new vegetation index called the yellow rust spore index(YRSI).The estimation accuracy and stability were evaluated using two years of leaf spectral data,and the results were compared with eight indices commonly used for yellow rust detection.The results showed that the use of the YRSI ranked first for estimating the disease ratio for the 2017 spectral data(R^(2)=0.710,RMSE=0.097)and outperformed the published indices(R^(2)=0.587,RMSE=0.120)for the validation using the 2002 spectral data.The random forest(RF),k-nearest neighbor(KNN),and support vector machine(SVM)algorithms were used to test the discrimination ability of the YRSI and the eight commonly used indices using a mixed dataset of yellow-rust-infested,healthy,and aphid–infested wheat spectral data.The YRSI provided the best performance.

关键词： Yellow rust spectral index fungal spores quantitative identification hyperspectral remote sensing winter wheat

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Analysis of Channeling-Path Phenomena in a Complex Fault-Block Reservoir with Low Recovery Factor and High Water-Cut Ratio

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Fluid Dynamics & Materials Processing 2023年第2期19卷 361-377页

作者： Qunyi Wang Xiaoli Ma Yongbin Bi Haiyan He Xiao Gu Tongjing Liu Lekun Zhao Jidong Oilfield Company Ltd.Exploration and Development Research Institute Tangshan063000China Unconventional Oil and Gas Institute China University of Petroleum(Beijing)Beijing102249China College of Petroleum Engineering China University of Petroleum(Beijing)Beijing102249China

Current methods for the analysis of channeling-path phenomena in reservoirs cannot account for the influence of time and space on the actual seepage behavior.In the present study,this problem is addressed considering actual production data and dynamic characteristic parameters quantitatively determined in the near wellbore area by fitting the water-cut curve of the well.Starting from the dynamic relationship between injection and production data,the average permeability is determined and used to obtain a real-time quantitative characterization of the seepage behavior of the channeling-path in the far wellbore area.For the considered case study(Jidong oilfield),it is found that the seepage capacity of the channeling-path in the far wellbore area is far less(10 times smaller)than that of the channeling-path in the near wellbore area.The present study and the proposed model(combining near wellbore area and far wellbore area real-time data)have been implemented to support the definition of relevant adjustment measures to ultimately improve oil recovery.

关键词： Complex fault-block reservoirs channeling path quantitative identification characteristic parameters dynamic inversion

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Research on identification Method of Argillaceous Interlayer in Compound Sand

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Open Journal of Geology 2023年第5期13卷 337-344页

作者： Yue Xie Liqin Gan Jingfu Deng Zhanhua Zhang Guanshan Yan Tianjin Branch of CNOOC Ltd. Tianjin China

For the compound sand body, the interlayer is an important factor affecting the adjustment of oil production structure and remaining oil distribution. According to the origin of argillaceous interlayer, the interlayer is divided into three types, including barriers between two single layers, intercalations between two single sands and intercalations in a single sand. In this study, the upper limit of physical properties of interlayer was obtained by analyzing the relationship between physical parameters and production index per-meter. The discriminant index and comprehensive discriminant chart of interlayer were obtained by grey correlation method, which realize the quantitative identification of different types of interlayer. The intercalations between two single sands in the target area are distributed almost in the whole area, which is one of the most important factors influencing the mining effect of compound sand, so the planar distribution is mainly aimed at it. Firstly, through cross-well comparison, we summarize three interlayer patterns, then establish their forward modeling, so as to obtain the vertical seismic characteristics of different patterns. Secondly, according to the thickness of intercalations between two single sands, we take the top of bottom sand as the baseline, extract the average amplitude attribute from the upper and lower 3 ms, then, according to the seismic section and planar characteristics of the well, the interlayer structures represented by different seismic section and planar characteristics are summarized. Finally, starting from the real drilling interlayer of the well, the planar spread of interlay can be obtained according to their variation trend and distribution.

关键词： Compound Sand Interlayer quantitative identification The Planar Distribution of Interlay

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地方政府债务风险的量化识别与防范策略

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财政与税务 2023年第4期

作者：郭玉清张妍薛琪琪

秉持底线思维防范地方政府债务风险冲击，是新时代重大风险防御攻坚的重要任务。本文考虑经济、财政、债务、体制四类因素，构建了中国地方政府债务风险预警指标体系，进而手工整理330个地级及以上城市数据样本，综合运用TOPSIS-熵值法... 详细信息

秉持底线思维防范地方政府债务风险冲击，是新时代重大风险防御攻坚的重要任务。本文考虑经济、财政、债务、体制四类因素，构建了中国地方政府债务风险预警指标体系，进而手工整理330个地级及以上城市数据样本，综合运用TOPSIS-熵值法和K-均值聚类法展开量化评估，从时、空维度识别出地方政府债务风险的演化趋势、分布规律和集聚特征。研究表明，我国地方政府债务风险整体可控，但风险在流动性和结构性层面凸显，东部和中部、东北和西部两大区域在风险程度、高险频次与空间集聚等方面的“俱乐部”分异现象非常显著。本文为防范债务风险凝聚扩散，提供了统筹推进治理转型、密切监测风险态势、设计区域差异化防范策略等政策建议。

关键词：地方政府债务风险 TOPSIS-熵值法量化识别防范策略　　risk caused by local governmental debt TOPSIS-entropy method quantitative identification preventive strategies

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双边市场的定性判断与定量识别：一个综述

产业经济

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产业经济 2013年第11期 1-18页

作者：傅联英骆品亮

双边市场是产业组织理论的新前沿，但目前尚缺乏统一的判断标准，导致双边市场概念在现实中有被滥用或误用的倾向，不利于双边平台企业商业模式的设计及相关规制政策的制定。本文从判别条件与识别方法两方面对双边市场进行正本清源：首... 详细信息

双边市场是产业组织理论的新前沿，但目前尚缺乏统一的判断标准，导致双边市场概念在现实中有被滥用或误用的倾向，不利于双边平台企业商业模式的设计及相关规制政策的制定。本文从判别条件与识别方法两方面对双边市场进行正本清源：首先，强调了辨识双边市场的重要性及其难点；然后，对“价格结构非中性说”与“交叉网络外部性说”进行比较分析，明确了双边市场的根本特征，进而提出两项定性判断基准；最后，系统论述了定量识别双边市场的检验方法。本文认为，交叉网络外部性是双边市场的标识特征；据此遵循逻辑演绎与实证检验相结合的策略，采用改进的结构化计量模型与归属曲线模型辨识双边市场可以满足理论基础的坚实性、因果效应的可识别性和计量模型的适切性。

关键词：双边市场定性判断定量识别　　two-sided markets qualitative judgment quantitative identification

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