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regularized quantile regression for SNP marker estimation of pig growth curves

Journal of Animal Science and Biotechnology 2017年第4期8卷 824-832页

作者： L.M.A.Barroso M.Nascimento A.C.C.Nascimento1 F.F.Silva N.V.L.Serao C.D.Cruz M.D.V.Resende F.L.Silva C.F.Azevedo P.S.Lopes S.E.F.Guimaraes Department of Statistics Federal University of Vicosa Av. P H Rolfs s/nUniversity Campus Vicosa MG 36570-000 Brazil Department of Animal Science Federal University of Vicosa Av. P H Rolfs s/n University CampusVicosa MG 36570-000 Brazil Department of Animal Science Iowa State University Kildee Hall 50011 Ames Iowa USA Department of General Biology Federal University of Vicosa Av. P H Rolfs s/n University CampusVicosa MG 36570-000 Brazil Embrapa Forestry Estrada da Ribeira km 111Colombo PR Brazil. Department of Plant Science Federal University of Vicosa Av. P H Rolfs s/n University Campus Vicosa MG 36570-000 Brazil

Background: Genomic growth curves are general y defined only in terms of population mean; an alternative approach that has not yet been exploited in genomic analyses of growth curves is the Quantile Regression(QR). This methodology allows for the estimation of marker effects at different levels of the variable of interest. We aimed to propose and evaluate a regularized quantile regression for SNP marker effect estimation of pig growth curves, as well as to identify the chromosome regions of the most relevant markers and to estimate the genetic individual weight trajectory over time(genomic growth curve) under different quantiles(levels).Results: The regularized quantile regression(RQR) enabled the discovery, at different levels of interest(quantiles), of the most relevant markers al owing for the identification of QTL regions. We found the same relevant markers simultaneously affecting different growth curve parameters(mature weight and maturity rate): two(ALGA0096701 and ALGA0029483)for RQR(0.2), one(ALGA0096701) for RQR(0.5), and one(ALGA0003761) for RQR(0.8). Three average genomic growth curves were obtained and the behavior was explained by the curve in quantile 0.2, which differed from the others.Conclusions: RQR allowed for the construction of genomic growth curves, which is the key to identifying and selecting the most desirable animals for breeding purposes. Furthermore, the proposed model enabled us to find, at different levels of interest(quantiles), the most relevant markers for each trait(growth curve parameter estimates) and their respective chromosomal positions(identification of new QTL regions for growth curves in pigs). These markers can be exploited under the context of marker assisted selection while aiming to change the shape of pig growth curves.

关键词： Genome association Growth curve Pig QTL regularized quantile regression

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regularized TWO-STAGE STOCHASTIC VARIATIONAL INEQUALITIES FOR COURNOT-NASH EQUILIBRIUM UNDER UNCERTAINTY

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Journal of Computational Mathematics 2019年第6期37卷 813-842页

作者： Jie Jiang Yun Shi Xiaozhou Wang Xiaojun Chen Department of Applied Mathematics The Hong Kong Polytechnic UniversityHong KongChina

A convex two-stage non-cooperative multi-agent game under uncertainty is formula ted as a two-stage stochastic variational inequality(SVI).Under standard assumptions,we provide sufficient conditions for the existence of solutions of the two-stage SVI and propose a regularized sample average approximation method for solving it.We prove the convergence of the method as the regularization parameter tends to zero and the sample size tends to infinity.Moreover,our approach is applied to a two-stage stochastic production and supply planning problem with homogeneous commodity in an oligopolistic market.Numerical results based on historical data in crude oil market are presented to demonstrate the effectiveness of the two-stage SVI in describing the market share of oil producing agents.

关键词： Two-stage stochastic variational inequalities Cournot-Nash equilibrium regularized method Progressive hedging method Uncertainty Oil market share.

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Dimensionality Reduction for Hyperspectral Data Based on Sample-Dependent Repulsion Graph regularized Auto-encoder

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Chinese Journal of Electronics 2017年第6期26卷 1233-1238页

作者： WANG Xuesong KONG Yi CHENG Yuhu School of Information and Control Engineering China University of Mining and Technology

To achieve high classification accuracy of hyperspectral data, a dimensionality reduction algorithm called Sample-dependent repulsion graph regularized auto-encoder(SRGAE) is proposed. Based on the sample-dependent graph, by applying the repulsion force to the samples from different classes but nearby, a sampledependent repulsion graph is built to make the samples from the same class will be pro jected to samples that are close-by and the samples from different classes will be pro jected to samples that are far away. The sampledependent repulsion graph can avoid the neighborhood parameter selection problem existing in the nearest neighborhood graph. By integrating advantages of deep learning and graph regularization technique, the SRGAE can maintain the learned deep features are consistent with the inherent manifold structure of the original hyperspectral data. Experimental results on two real hyperspectral data show that, when compared with some popular dimensionality reduction algorithms, the proposed SRGAE can yield higher classification accuracy.

关键词： Hyperspectral data Dimensionality reduction Sample-dependent repulsion graph regularized Auto-encoder

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α-times Integrated regularized Cosine Functions and Second Order Abstract Cauchy Problems

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Journal of Donghua University(English Edition) 2001年第1期18卷 51-54页

作者： Zhang Jizhou(张寄洲) Tao Youshan(陶有山) College of Mathematics Science Shanghai Normal University Shanghai 200234 Department of Applied Mathematics Dong Hua University Shanghai 200051

In this paper, α -times integrated C-regularized cosine functions and mild α-times integrated C-existence families of second order are introduced. Equivalences are proved among α -times integrated C-regularized cosine function for a linear operator A, C-wellposed of (α + 1)-times abstract Cauchy problem and mild α -times integrated C-existence family of second order for A when the commutable condition is satisfied. In addition, if A = C-1AC, they are also equivalent to A generating the α -times integrated C-regularized cosine finction.The characterization of an exponentially botnded mild α -times integrated C-existence family of second order is given out in terms of a Laplace transform.

关键词： α-times integrated regularized cosine function, mild α-times integrated C-existence family of second order, C-wellposed, second order abstract Cauchy problem.

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LKLR: A Local Tangent Space-Alignment Kernel Least-Squares Regression Algorithm

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Tsinghua Science and Technology 2019年第4期24卷 389-399页

作者： Chao Tan Genlin Ji the School of Computer Science and Engineering Southeast University the School of Computer Science and Technology Nanjing Normal University the School of Computer Science and Technology Nanjing Normal University

In the fields of machine learning and data mining, label learning is a nascent area of research, and within this paradigm, there is much room for improving multi-label manifold learning algorithms for high-dimensional data. Thus far, researchers have experimented with mapping relationships from the feature space to the traditional logical label space(using neighbors in the label space, for example, to predict logical label vectors from the feature space's manifold structure). Here we combine the feature manifold's and label space's local topological structures to reconstruct the label manifold. To achieve this, we use a nonlinear manifold learning algorithm to transform the local topological structure from the feature space to the label space. Our algorithm adopts a regularized leastsquares kernel method to realize the reconstruction process, employing an optimization function to find the best solution. Extensive experiments show that our algorithm significantly improves multi-label manifold learning in terms of learning accuracy and time complexity.

关键词： multi-label manifold learning local topological structure regularized least squares kernel method

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EXISTENCE AND CONTROLLABILITY FOR NONLINEAR FRACTIONAL CONTROL SYSTEMS WITH DAMPING IN HILBERT SPACES

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Acta Mathematica Scientia 2019年第1期39卷 229-242页

作者：李秀文刘振海李景 Chris TISDELL School of Science Nanjing University of Sciences and Technology Guangxi Colleges and Universities Key Laboratory of Complex System Optimization and Big Data Processing Yulin Normal University Hunan Province Key Laboratory of Mathematical Modelling and Analysis in Engineering Department of Mathematics and Statistics Changsha University of Science and Technology Faculty of Science The University of New South Wales UNSW

In this paper, we are concerned with the existence of mild solution and controllability for a class of nonlinear fractional control systems with damping in Hilbert spaces.Our first step is to give the representation of mild solution for this control system by utilizing the general method of Laplace transform and the theory of(α, γ)-regularized families of operators. Next, we study the solvability and controllability of nonlinear fractional control systems with damping under some suitable sufficient conditions. Finally, two examples are given to illustrate the theory.

关键词： existence controllability fractional control systems damping regularized resolvent family

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A Novel Interacting Multiple-Model Method and Its Application to Moisture Content Prediction of ASP Flooding

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Computer Modeling in Engineering & Sciences 2018年第1期114卷 95-116页

作者： Shurong Li Yulei Ge Renlin Zang Automation School Beijing University of Posts and TelecommunicationsBeijingChina College of Information and Control Engineering China University of Petroleum(East China)QingdaoChina

In this paper,an interacting multiple-model(IMM)method based on datadriven identification model is proposed for the prediction of nonlinear dynamic systems.Firstly,two basic models are selected as combination components due to their proved effectiveness.One is Gaussian process(GP)model,which can provide the predictive variance of the predicted output and only has several optimizing parameters.The other is regularized extreme learning machine(RELM)model,which can improve the overfitting problem resulted by empirical risk minimization principle and enhances the overall generalization performance.Then both of the models are updated continually using meaningful new data selected by data selection methods.Furthermore,recursive methods are employed in the two models to reduce the computational burden caused by continuous renewal.Finally,the two models are combined in IMM algorithm to realize the hybrid prediction,which can avoid the error accumulation in the single-model prediction.In order to verify the performance,the proposed method is applied to the prediction of moisture content of alkali-surfactant-polymer(ASP)flooding.The simulation results show that the proposed model can match the process very well.And IMM algorithm can outperform its components and provide a nice improvement in accuracy and robustness.

关键词： Interacting multiple model regularized extreme learning machine gaussian process moisture content of ASP flooding

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Applications of semigroups of operators to non-elliptic differential operators

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Chinese Science Bulletin 2000年第8期45卷 673-682页

作者： ZHENG QuanDepartment of Mathematics, Huazhong University of Science and Technology, Wuhan 430074, China Department of Mathematics Huazhong University of Science and Technology Wuhan China

This paper treats systematically the semigroup method of non-elliptic differential operators, which was developed in the last ten years. In particular, a review of the applications of regularized semigroups to non-elliptic differential operators with constant coefficients or time-dependent coefficients, parabolic systems, correct systems, abstract differential operators and pseudodifferential operators is given here. It is also shown that the regularized semigroup is an appropriate tool for non-elliptic differential operators and is far superior to the integrated semigroup approach.

关键词： differential operator regularized semigroup integrated semigroup initial value problem Fourier multiplier.

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Some characteristics and evolution of the internal soliton in the northern South China Sea

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Chinese Science Bulletin 2002年第1期47卷 21-27页

作者： Cai, SQ Gan, ZJ Long, XM Chinese Acad Sci LED S China Sea Inst Oceanol Guangzhou 510301 Peoples R China

Based on the observational data of an internal soliton in the northern South China Sea (SCS) on June 14, 1998, the possible source of the internal soliton is analyzed, and some of its characteristic parameters such as phase speed, wave length, etc. are computed. Based on the analyses of the vertical modes of the internal wave, the characteristics of the wave-induced current during the propagation of the internal soliton are studied. A regularized long wave (RLW) equation numerical model considering effects of multi-fac-tors is employed, and the observed environmental parame-ters are used as the initial conditions to simulate the propa-gation and evolution of the internal soliton in the continental shelf of the northern SCS.

关键词： internal soliton wave-induced current regularized long wave equation numerical simulation.

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The Convergence Rate of Ergodic Limits for regularized Resolvent Families

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Journal of Donghua University(English Edition) 2004年第6期21卷 109-114页

作者：张寄洲裔永刚 Department of Applied Mathematics Shanghai Normal UniversityShanghai 200234professor Department of Applied Mathematics Shanghai Normal UniversityShanghai 200234

This paper is concerned with the convergence rates of ergodic limits and approximation for regularized resolvent families for a linear Volterra integral equation. The results contain C 0-semigroups, cosine operator fu... 详细信息

关键词： regularized resolvent families, convergence, ergodic limit,K-functional

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