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An Improved non-parametric method for Multiple Moving Objects Detection in the Markov Random Field

Computer Modeling in Engineering & Sciences 2020年第7期124卷 129-149页

作者： Qin Wan Xiaolin Zhu Yueping Xiao Jine Yan Guoquan Chen Mingui Sun College of Electric and Information Engineering Hunan Institute of EngineeringXiangtan411104China National Engineering Research Laboratory for Robot Vision Perception and Control Hunan UniversityChangshaChina The Laboratory for Computational Neuroscience University of PittsburghPittsburghPA 15260USA

Detecting moving objects in the stationary background is an important problem in visual surveillance ***,the traditional background subtraction method fails when the background is not completely stationary and involves certain dynamic *** this paper,according to the basic steps of the background subtraction method,a novel non-parametric moving object detection method is proposed based on an improved ant colony algorithm by using the Markov random ***,the contributions are as follows:1)A new nonparametric strategy is utilized to model the background,based on an improved kernel density estimation;this approach uses an adaptive bandwidth,and the fused features combine the colours,gradients and positions.2)A Markov random field method based on this adaptive background model via the constraint of the spatial context is proposed to extract objects.3)The posterior function is maximized efficiently by using an improved ant colony system *** experiments show that the proposed method demonstrates a better performance than many existing state-of-the-art methods.

关键词： Object detection non-parametric method markov random field

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Measuring technical efficiency of potato production in Iran using robust data envelopment analysis

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Information Processing in Agriculture 2015年第1期2卷 6-14页

作者： Mostafa Mardani Mashallah Salarpour Department of Agricultural Economics Faculty of AgricultureUniversity of ZabolZabolIran

A non-parametric method of data envelopment analysis(DEA)was applied to analyze the technical and scale efficiency of potato production in 23 Iranian *** many real applications,inputs and outputs may be *** the present study,a robust DEA(RDEA)optimization framework was used to concentrate on DEA with uncertain *** method was based on six inputs(human labor rent,land rent,diesel and machinery rent,irrigation water cost,fertilizer cost,pesticide cost)and the single output of potato gross *** proposed DEA for 23 Iranian potato-producing provinces reveals that the average technical efficiency is 90%and scale efficiency is 97%.This suggests that inefficient provinces can potentially reduce their overall costs for potato production.A Monte Carlo simulation was used to compute the conformity of the rankings from the RDEA model with reality to illustrate the importance of varying the level of efficiency for different levels of conservatism.

关键词： non-parametric method Robust optimization Monte Carlo simulation Cost of potato production

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AN OPERATIONAL STATISTICAL SCHEME FOR TROPICAL CYCLONE INDUCED RAINFALL FORECAST

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Journal of Tropical Meteorology 2015年第2期21卷 101-110页

作者：李晴岚兰红平陈仲良曹春燕李程王兴宝 Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen Meteorological Bureau Laboratory for Atmospheric Research Department of Physics and Materials Science City University of Hong Kong Centre for Australian Weather and Climate Research Bureau of Meteorology Melbourne VIC 3001 Australia

A non-parametric method is used in this study to analyze and predict short-term rainfall due to tropical cyclones(TCs) in a coastal meteorological station. All 427 TCs during 1953-2011 which made landfall along the Southeast China coast with a distance less than 700 km to a certain meteorological station- Shenzhen are analyzed and grouped according to their landfalling direction, distance and intensity. The corresponding daily rainfall records at Shenzhen Meteorological Station(SMS) during TCs landfalling period(a couple of days before and after TC landfall) are collected. The maximum daily rainfall(R-24) and maximum 3-day accumulative rainfall(R-72) records at SMS for each TC category are analyzed by a non-parametric statistical method, percentile estimation. The results are plotted by statistical boxplots, expressing in probability of precipitation. The performance of the statistical boxplots is evaluated to forecast the short-term rainfall at SMS during the TC seasons in 2012 and 2013. Results show that the boxplot scheme can be used as a valuable reference to predict the short-term rainfall at SMS due to TCs landfalling along the Southeast China coast.

关键词： tropical cyclone rainfall forecast non-parametric method boxplot

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Recovering implied risk-neutral probability density function using SVR

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Journal of Southeast University(English Edition) 2010年第3期26卷 489-493页

作者：胡小平崔海蓉朱丽华王新燕东南大学经济管理学院南京211189 南京农业大学工学院南京210032

Using support vector regression （SVR）, a novel non-parametric method for recovering implied risk-neutral probability density function （IRNPDF） is investigated by solving linear operator equations. First, the SVR principle for function approximation is introduced, and an SVR method for solving linear operator equations with knowing some values of the right-hand function and without knowing its form is depicted. Then, the principle for solving the IRNPDF based on SVR and the method for constructing cross-kernel functions are proposed. Finally, an empirical example is given to verify the validity of the method. The results show that the proposed method can overcome the shortcomings of the traditional parametric methods, which have strict restrictions on the option exercise price; meanwhile, it requires less data than other non-parametric methods, and it is a promising method for the recover of IRNPDF.

关键词： support vector regression option prices implied risk-neutral probability linear operator equation non-parametric method

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A review on Gaussian Process Latent Variable Models

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CAAI Transactions on Intelligence Technology 2016年第4期1卷 366-376页

作者： Ping Li Songcan Chen College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing 210016 China

Gaussian Process Latent Variable Model （GPLVM）, as a flexible bayesian non-parametric modeling method, has been extensively studied and applied in many learning tasks such as Intrusion Detection, Image Reconstruction, Facial Expression Recognition, Human pose estimation and so on. In this paper, we give a review and analysis for GPLVM and its extensions. Firstly, we formulate basic GPLVM and discuss its relation to Kernel Principal Components Analysis. Secondly, we summarize its improvements or variants and propose a taxonomy of GPLVM related models in terms of the various strategies that be used. Thirdly, we provide the detailed formulations of the main GPLVMs that extensively developed based on the strategies described in the paper. Finally, we further give some challenges in next researches of GPLVM.

关键词： GPLVM non-parametric method Gaussian process

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