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Inference and Modeling with Log-concave Distributions

STATISTICAL SCIENCE 2009年第3期24卷 319-327页

作者： Walther, Guenther Stanford Univ Dept Stat Stanford CA 94305 USA

Log-concave distributions are an attractive choice for modeling and inference, for several reasons: The class of log-concave distributions contains most of the commonly used parametric distributions and thus is a rich and flexible nonparametric class of distributions. Further, the MLE exists and can be computed with readily available algorithms. Thus, no tuning parameter, such as a bandwidth, is necessary for estimation. Due to these attractive properties, there has been considerable recent research activity concerning the theory and applications of log-concave distributions. This article gives a review of these results.

关键词： Nonparametric density estimation shape constraint log-concave density Polya frequency function strongly unimodal iterative convex minorant algorithm active set algorithm

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Aerodynamic Characteristics and Noise Collaborative Optimization of an Airfoil

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Wuhan University Journal of Natural Sciences 2020年第3期25卷 238-246页

作者： ZHAN Zhihuan GU Chaojie XIAO Qing CHEN Dongyang Beijing Research Institute of Mechanical&Electrical Technology Beijing 100041China College of Electrical Energy and Power EngineeringYangzhou UniversityYangzhou 225127JiangsuChina China Ship Development and Design Center Wuhan 430064HubeiChina

Aerodynamic noise is the main problem restricting its development nowadays in green energy,ocean engineering and aerospace *** order to limit the aerodynamic noise of an airfoil structure,a method is proposed in this paper by designing low noise *** method optimized the aerodynamic noise of two-dimensional airfoil,and considered the aerodynamic performance of the airfoil at the same *** on Joukowski conformal transformation,airfoil geometry is parameterized ***,the optimization model taking the lift-to-drag ratio and airfoil self-noise as the design objective,is established to modify the airfoil by active set algorithm until the airfoil can satisfy the design ***,the noise of the optimized airfoil is verified according to the prediction theory of airfoil ***,the relationship between airfoil geometry and noise is *** results show that the lift-to-drag ratio of the optimized airfoil increased,and the noise also ***,the optimization method can be used to address special design of low-noise ***,the optimization method in this paper can provide reference for improving lift-to-drag ratio and reducing noise of the airfoil in aircraft and submarine rudder system.

关键词： wind turbine blade lift-to-drag ratio aerodynamic noise optimization design of airfoil active set algorithm

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The Stokes Flow with Friction

The Stokes Flow with Friction

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International Conference on Numerical Analysis and Applied Mathematics (ICNAAM)

作者： Kucera, Radek Satek, Vaclav Jarosova, Marta Kozubek, Tomas VSB Tech Univ Ostrava IT4Innovat Ostrava 70833 Czech Republic

ISBN: (纸本)9780735412873

Efficient methods for solving the Stokes problem with a friction effect simulated by the slip boundary condition are developed. The dual formulation of the problem arising from the finite element approximation leads to the minimization of the strictly quadratic function with few unknowns constrained by simple bounds. Two solution algorithms highly efficient in contact solid mechanics are tested: the active set strategy and the path-following variant of the interior point method. Numerical experiments conclude the paper.

关键词： Stokes Problem Slip Boundary Condition active set algorithm Interior Point Method

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SPARSE BRANCH AND BOUND FOR EXACT OPTIMIZATION OF L0-NORM PENALIZED LEAST SQUARES

SPARSE BRANCH AND BOUND FOR EXACT OPTIMIZATION OF L0-NORM PE...

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IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Ben Mhenni, Ramzi Bourguignon, Sebastien Mongeau, Marcel Ninin, Jordan Carfantan, Herve Ecole Cent Nantes LS2N 1 Rue Noe F-44321 Nantes France Univ Toulouse ENAC 7 Ave Edouard Belin F-31055 Toulouse France ENSTA Bretagne Lab STICC 2 Rue Francois Verny F-29806 Brest 9 France Univ Toulouse CNRS UPs IRAPCNES 14 Ave Edouard Belin F-31400 Toulouse France

ISBN: (纸本)9781509066315

We propose a global optimization approach to solve l(0)-norm penalized least-squares problems, using a dedicated branchand-bound methodology. A specific tree search strategy is built, with branching rules inspired from greedy exploration techniques. We show that the subproblem involved at each node can be evaluated via l(1)-norm-based optimization problems with box constraints, for which an active-set algorithm is built. Our method is able to solve exactly moderate-size, yet difficult, sparse approximation problems, without resorting to mixed-integer programming (MIP) optimization. In particular, it outperforms the generic MIP solver CPLEX.

关键词： Sparse approximation Inverse problems Optimization Branch & Bound active set algorithm

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Shipping network design-infrastructure investment joint optimization model: a case study of West Africa

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MARITIME POLICY & MANAGEMENT 2022年第5期49卷 620-646页

作者： Xin, Xu Wang, Xiaoli Ma, Lijun Chen, Kang Ye, Maoyao Tongji Univ Sch Econ & Management Siping Rd 1500 Shanghai 200092 Peoples R China Dalian Maritime Univ Sch Maritime Econ & Management Dalian Peoples R China Tongji Univ Coll Elect & Informat Engn Shanghai Peoples R China

Since the proposal of the Belt and Road initiative in March 2015, the Chinese government has continued to increase its investment in transportation infrastructure construction in West African countries. To realize the scientific decision-making process for large-scale investment, this paper establishes a shipping network design-infrastructure investment joint optimization model. The abovementioned model aims to find the minimum generalized transportation cost in the study area and jointly optimizes the construction scheme of the regional inland transportation network (i.e., railway network), the expansion scheme of the port (i.e., container port) throughput capacity, and the operation scheme of the shipping network (i.e., container shipping network) given a limited budget. Based on the framework of the active set algorithm, an algorithm that can explore the local optimal solution of the abovementioned model is designed. Taking China-West Africa transportation as the research object, numerical experiments are carried out to verify the effectiveness of the model and algorithm. Two types of sensitivity analyses for different investment scales and origin-destination demand are designed. The results show that the proposed model and algorithm can effectively solve the abovementioned problem and can provide decision-making support for the Chinese government in formulating reasonable investment schemes for West Africa. This paper is a revised and expanded version of a paper entitled, 'Shipping network design-infrastructure investment joint optimization model' presented at the 3(rd) International Conference of the Yangtze River Research and Innovation Belt, Ningbo, China;5-7 November 2020.

关键词： container shipping shipping network design infrastructure investment West Africa active set algorithm user equilibrium

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A NONLINEAR LEAST-SQUARES CONVEXITY ENFORCING C⁰ INTERIOR PENALTY METHOD FOR THE MONGE–AMPÈRE EQUATION ON STRICTLY CONVEX SMOOTH PLANAR DOMAINS

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Communications of the American Mathematical Society 2024年第14期4卷 607-640页

作者： Brenner, Susanne C. Sung, Li-Yeng Tan, Zhiyu Zhang, Hongchao Department of Mathematics and Center for Computation and Technology Louisiana State University Baton Rouge 70803 LA United States Center for Computation and Technology Louisiana State University Baton Rouge LA United States School of Mathematical Sciences and Fujian Provincial Key Laboratory on Mathematical Modeling and High Performance Scientific Computing Xiamen University Fujian 361005 China

We construct a nonlinear least-squares finite element method for computing the smooth convex solutions of the Dirichlet boundary value problem of the Monge-Ampère equation on strictly convex smooth domains in R². It is based on an isoparametric C⁰ finite element space with exotic degrees of freedom that can enforce the convexity of the approximate solutions. A priori and a posteriori error estimates together with corroborating numerical results are presented. © 2024 by the author(s) under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License (CC BY NC ND 4.0)

关键词： Monge-Ampère equation strictly convex smooth domains nonlinear least-squares convexity enforcing 𝐶⁰ interior penalty method enhanced cubic Lagrange finite elements isoparametric a priori and a posteriori error estimates active set algorithm

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Chaos-infused wind power integration in the grey wolf optimal paradigm for combine thermal-wind power plant systems

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FRONTIERS IN ENERGY RESEARCH 2024年 12卷

作者： Wadood, Abdul Khan, Babar Sattar Khurshaid, Tahir Kim, Ki-Chai Rhee, Sang Bong Univ Tabuk Renewable Energy & Environm Technol Ctr Tabuk Saudi Arabia Univ Tabuk Fac Engn Elect Engn Dept Tabuk Saudi Arabia Air Univ Islamabad Dept Elect Engn Kamra Pakistan Univ Engn & Technol Peshawar Dept Elect Energy Syst Engn USPCAS E Peshawar Khyber Pakhtunk Pakistan Comsats Univ Dept Elect & Comp Engn Lahore Pakistan Yeungnam Univ Dept Elect Engn Gyongsan South Korea

This research presents a novel methodology for tackling the combined thermal-wind economic load dispatch (ELD) issue in contemporary power system. The proposed approach involves hybridizing active-set algorithm (ASA), interior point algorithm (IPA) and sequential quadratic programming (SQP) into grey wolf optimization (GWO) algorithm, while effectively incorporating the intricacies associated with renewable energy sources (RES). A more accurate model is made possible by hybridization for complex systems with memory and hereditary characteristics. The GWO is used as a tool for global search while ASA, IPA and SQP methods are used for rapid local optimization mechanism. The performance evaluation of the design heuristics is carried out on 37 thermal and 3 wind power generating units and outcomes endorse the effectiveness of the proposed scheme over state-of-the-art counterparts. The worthy performance is further validated on statistical assessments in case of thermal-wind integrated ELD problem in terms of measure of central tendency and variation on cost and complexity indices.

关键词： grey wolf optimization interior point algorithm active set algorithm sequential quadratic programming economic load dispatch problem stochastic wind

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Integrated meta-heuristics finite difference method for the dynamics of nonlinear unipolar electrohydrodynamic pump flow model

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APPLIED SOFT COMPUTING 2020年第PartA期97卷 106791-106791页

作者： Jadoon, Ihtesham Ahmed, Ashfaq Rehman, Ata Ur Shoaib, Muhammad Raja, Muhammad Asif Zahoor COMSATS Univ Islamabad Dept Elect & Comp Engn Wah Campus Rawalpindi Pakistan Khalifa Univ Dept Elect Engn & Comp Sci Abu Dhabi U Arab Emirates COMSATS Univ Islamabad Dept Elect & Comp Engn Campus Attock Attock Pakistan COMSATS Univ Islamabad Dept Math Campus Attock Attock Pakistan Natl Yunlin Univ Sci & Technol Future Technol Res Ctr 123 Univ RdSect 3 Touliu 64002 Yunlin Taiwan

In this study, a novel design of integrated biological inspired computational heuristics is presented for the dynamics of nonlinear unipolar electrohydrodynamic (UP-EHD) pump flow model by exploiting the competency of finite difference method (FDM) for discretization, global search viability of genetic algorithms (GAs) and local search efficiency of active-set method (ASM), i.e., FDM-GA-ASM. The FDM is incorporated to transform the differential equations of the UP-EHD pump flow model into a system of nonlinear algebraic equations. The cost function is constructed through the mean-square residual error by mimicking forward, central and backward difference schemes viable for a broader range of physical models. The optimum solution is achieved by the integration of global search with GAs and local search of ASM for speedy refinements. The designed stochastic numerical solver FDM-GA-ASM investigates the critical physical parameters, i.e., charge density, electric field and electric potential by varying electrical slip, Reynolds number and source number of the UP-EHD model. Statistical observations in terms of probability plots, histogram illustrations, boxplots for the cost function, mean absolute error, root mean squared error and Nash-Sutcliffe efficiency metrics are used to validate the efficiency of the FDM-GAASM scheme for the three variants of the UP-EHD model. The designed FDM-GA-ASM is a promising numerical computing solver for nonlinear differential systems in engineering and technology. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Bio-inspired heuristics Unipolar pump flow Electrohydrodynamic Genetic algorithm active set algorithm Nonlinear systems

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SUnAA: Sparse Unmixing Using Archetypal Analysis

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IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 2023年 20卷 1页

作者： Rasti, Behnood Zouaoui, Alexandre Mairal, Julien Chanussot, Jocelyn Helmholtz Inst Freiberg Resource Technol Helmholtz Zentrum Dresden Rossendorf Machine Learning Grp D-09599 Freiberg Germany Univ Grenoble Alpes Inria CNRS Grenoble INPLJK F-38000 Grenoble France

This letter introduces a new sparse unmixing technique using archetypal analysis (SUnAA). First, we design a new model based on archetypal analysis (AA). We assume that the endmembers of interest are a convex combination of endmembers provided by a spectral library and that the number of endmembers of interest is known. Then, we propose a minimization problem. Unlike most conventional sparse unmixing methods, here the minimization problem is nonconvex. We minimize the optimization objective iteratively using an active set algorithm. Our method is robust to the initialization and only requires the number of endmembers of interest. SUnAA is evaluated using two simulated datasets for which results confirm its better performance over other conventional and advanced techniques in terms of signal-to-reconstruction error (SRE). SUnAA is also applied to Cuprite dataset and the results are compared visually with the available geological map provided for this dataset. The qualitative assessment demonstrates the successful estimation of the minerals abundances and significantly improves the detection of dominant minerals compared to the conventional regression-based sparse unmixing methods. The Python implementation of SUnAA can be found at: https://***/BehnoodRasti/SUnAA.

关键词： active set algorithm archetypal analysis (AA) hyperspectral imaging semi-supervised unmixing sparse unmixing

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Direct Position Determination of Unknown Signals in the Presence of Multipath Propagation

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SENSORS 2018年第3期18卷 892-892页

作者： Du, Jianping Wang, Ding Yu, Wanting Yu, Hongyi Natl Digital Switching Syst Engn & Technol Res Ct Zhengzhou 450002 Henan Peoples R China

A novel geolocation architecture, termed "Multiple Transponders and Multiple Receivers for Multiple Emitters Positioning System (MTRE)" is proposed in this paper. Existing Direct Position Determination (DPD) methods take advantage of a rather simple channel assumption (line of sight channels with complex path attenuations) and a simplified MUltiple SIgnal Classification (MUSIC) algorithm cost function to avoid the high dimension searching. We point out that the simplified assumption and cost function reduce the positioning accuracy because of the singularity of the array manifold in a multi-path environment. We present a DPD model for unknown signals in the presence of Multi-path Propagation (MP-DPD) in this paper. MP-DPD adds non-negative real path attenuation constraints to avoid the mistake caused by the singularity of the array manifold. The Multi-path Propagation MUSIC (MP-MUSIC) method and the active set algorithm (ASA) are designed to reduce the dimension of searching. A Multi-path Propagation Maximum Likelihood (MP-ML) method is proposed in addition to overcome the limitation of MP-MUSIC in the sense of a time-sensitive application. An iterative algorithm and an approach of initial value setting are given to make the MP-ML time consumption acceptable. Numerical results validate the performances improvement of MP-MUSIC and MP-ML. A closed form of the Cramer-Rao Lower Bound (CRLB) is derived as a benchmark to evaluate the performances of MP-MUSIC and MP-ML.

关键词： direct position determination MUSIC algorithm maximum likelihood estimation convex QP multi-path geolocation active set algorithm

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