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Artykuły w czasopismach na temat „CONEX framework”

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Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 20 lutego 2023

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1

Fang, Zheng, i Juwon Seo. "A Projection Framework for Testing Shape Restrictions That Form Convex Cones". Econometrica 89, nr 5 (2021): 2439–58. http://dx.doi.org/10.3982/ecta17764.

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This paper develops a uniformly valid and asymptotically nonconservative test based on projection for a class of shape restrictions. The key insight we exploit is that these restrictions form convex cones, a simple and yet elegant structure that has been barely harnessed in the literature. Based on a monotonicity property afforded by such a geometric structure, we construct a bootstrap procedure that, unlike many studies in nonstandard settings, dispenses with estimation of local parameter spaces, and the critical values are obtained in a way as simple as computing the test statistic. Moreover, by appealing to strong approximations, our framework accommodates nonparametric regression models as well as distributional/density‐related and structural settings. Since the test entails a tuning parameter (due to the nonstandard nature of the problem), we propose a data‐driven choice and prove its validity. Monte Carlo simulations confirm that our test works well.

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2

Wiecek, Margaret M. "Advances in Cone-Based Preference Modeling for Decision Making with Multiple Criteria". Decision Making in Manufacturing and Services 1, nr 2 (11.10.2007): 153–73. http://dx.doi.org/10.7494/dmms.2007.1.2.153.

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Decision making with multiple criteria requires preferences elicited from the decision maker to determine a solution set. Models of preferences, that follow upon the concept of nondominated solutions introduced by Yu (1974), are presented and compared within a unified framework of cones. Polyhedral and nonpolyhedral, convex and nonconvex, translated, and variable cones are used to model different types of preferences. Common mathematical properties of the preferences are discussed. The impact of using these preferences in decision making is emphasized.

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3

Kojima, Masakazu, Sunyoung Kim i Hayato Waki. "A GENERAL FRAMEWORK FOR CONVEX RELAXATION OF POLYNOMIAL OPTIMIZATION PROBLEMS OVER CONES". Journal of the Operations Research Society of Japan 46, nr 2 (2003): 125–44. http://dx.doi.org/10.15807/jorsj.46.125.

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4

Ohta, Tomoyuki, Tatsuki Yamazaki, Shinnosuke Murakami, Ryoichi Mukai i Yoshiaki Kakuda. "Evaluation framework for simulating MANET-based systems". IEICE Communications Express 10, nr 7 (1.07.2021): 404–8. http://dx.doi.org/10.1587/comex.2021xbl0089.

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Lewkowicz, Izchak. "Convex invertible cones of matrices — a unified framework for the equations of Sylvester, Lyapunov and Riccati". Linear Algebra and its Applications 286, nr 1-3 (styczeń 1999): 107–33. http://dx.doi.org/10.1016/s0024-3795(98)10164-7.

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6

Taenaka, Yuzo, i Kazuya Tsukamoto. "An efficient traffic management framework for multi-channel wireless backbone networks". IEICE Communications Express 3, nr 3 (2014): 98–103. http://dx.doi.org/10.1587/comex.3.98.

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7

Rashid, Saima, Humaira Kalsoom, Zakia Hammouch, Rehana Ashraf, Dumitru Baleanu i Yu-Ming Chu. "New Multi-Parametrized Estimates Having pth-Order Differentiability in Fractional Calculus for Predominating ℏ-Convex Functions in Hilbert Space". Symmetry 12, nr 2 (2.02.2020): 222. http://dx.doi.org/10.3390/sym12020222.

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In Hilbert space, we develop a novel framework to study for two new classes of convex function depending on arbitrary non-negative function, which is called a predominating ℏ-convex function and predominating quasiconvex function, with respect to η , are presented. To ensure the symmetry of data segmentation and with the discussion of special cases, it is shown that these classes capture other classes of η -convex functions, η -quasiconvex functions, strongly ℏ-convex functions of higher-order and strongly quasiconvex functions of a higher order, etc. Meanwhile, an auxiliary result is proved in the sense of κ -fractional integral operator to generate novel variants related to the Hermite–Hadamard type for p t h -order differentiability. It is hoped that this research study will open new doors for in-depth investigation in convexity theory frameworks of a varying nature.

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8

Saha, Sourav, Sahibjot Kaur, Jayanta Basak i Priya Ranjan Sinha Mahapatra. "A Computer Vision Framework for Automated Shape Retrieval". American Journal of Advanced Computing 1, nr 1 (1.01.2020): 1–15. http://dx.doi.org/10.15864/ajac.1108.

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With the increasing number of images generated every day, textual annotation of images for image mining becomes impractical and inefficient. Thus, computer vision based image retrieval has received considerable interest in recent years. One of the fundamental characteristics of any image representation of an object is its shape which plays a vital role to recognize the object at primitive level. Keeping this view as the primary motivational focus, we propose a shape descriptive frame work using a multilevel tree structured representation called Hierarchical Convex Polygonal Decomposition (HCPD). Such a frame work explores different degrees of convexity of an object’s contour-segments in the course of its construction. The convex and non-convex segments of an object’s contour are discovered at every level of the HCPD-tree generation by repetitive convex-polygonal approximation of contour segments. We have also presented a novel shape-string-encoding scheme for representing the HCPD-tree which allows us touse the popular concept of string-edit distance to compute shape similarity score between two objects. The proposed framework when deployed for similar shape retrieval task demonstrates reasonably good performance in comparison with other popular shape-retrieval algorithms.

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9

Mondal, Sourav, Goutam Das i Elaine Wong. "An Analytical Cost-Optimal Cloudlet Placement Framework over Fiber-Wireless Networks with Quasi-Convex Latency Constraint". Electronics 8, nr 4 (5.04.2019): 404. http://dx.doi.org/10.3390/electronics8040404.

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To meet the low-latency constraints arising from future smart mobile devices, Internet-of-Things, and 5G applications, major interest is currently given to the integration of centralized cloud computing and distributed edge computing infrastructures to deliver higher performance and reliability to edge devices in accessing mobile cloud services. The three-tier network architecture arising from cloud, cloudlet, and edge-devices can handle miscellaneous latency requirements for both latency-sensitive and latency-tolerant applications more efficiently than conventional two-tier networks. In this paper, we primarily focus on the static cloudlet network planning problem and propose an analytical hybrid cost-optimization framework for optimal cloudlet placement. We formulate this problem as a convex optimization problem and solve by using Karush-Kuhn-Tucker (KKT) conditions, and show that this framework can be evaluated without any scalability issues observed with integer programming based frameworks for large datasets. Moreover, we derive user-friendly closed form expressions that provide a first-hand estimation of cloudlet deployment cost depending on a few important network parameters like split-ratio, population density, and network bandwidth. Finally, we also show that the optimal solution of this analytical framework can be considered as a tight lower bound of the optimal solutions of integer programming based frameworks and makes a better cloudlet installation cost estimation compared to other existing frameworks.

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10

Sasaki, Sho, Yuichi Miyaji i Hideyuki Uehara. "A novel framework of routing policy for energy-efficient wireless sensor networks: Progress-based nearest forwarding". IEICE Communications Express 6, nr 3 (2017): 109–14. http://dx.doi.org/10.1587/comex.2016xbl0176.

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11

Al-Matouq, Ali Ahmed. "A Convex LASSO Framework for Linear Timetabling". IEEE Access 8 (2020): 167475–89. http://dx.doi.org/10.1109/access.2020.3019598.

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12

Shaker, Hamid Reza, i Rafael Wisniewski. "Switched Systems Reduction Framework Based on Convex Combination of Generalized Gramians". Journal of Control Science and Engineering 2009 (2009): 1–11. http://dx.doi.org/10.1155/2009/710478.

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A general method for model-order reduction of switched linear dynamical systems is presented. The proposed technique uses convex generalized gramian which is a convex combination of the generalized gramians. It is shown that different classical reduction methods can be developed into the generalized gramian framework for model reduction of linear systems and further for the reduction of switched systems by construction of the convex generalized gramian. Balanced reduction within specified frequency bound is taken as an example which is developed within this framework. In order to avoid numerical instability and also to increase the numerical efficiency, convex generalized gramian-based Petrov-Galerkin projection is constructed instead of the similarity transform approach for reduction. It is proven that the method preserves the stability of the original switched system at least for stabilizing switching signal and it is also less conservative than the method which is based on the common generalized gramian. Some discussions on the coefficient of the vertices of the convex variables are presented. The performance of the proposed method is illustrated by numerical examples.

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13

Zhu, Hanxin, Tao Yu, Weicong Wu i Zhuohuan Li. "Distributed Optimal Scheduling of Electricity–Gas–Heating System Based on Improved Alternating Direction Method of Multipliers". Applied Sciences 10, nr 4 (11.02.2020): 1214. http://dx.doi.org/10.3390/app10041214.

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With the joint optimization of the electricity–gas–heating system (EGHS) attracting more and more attention, a distributed optimized scheduling framework for EGHS based on an improved alternating direction method of multipliers (ADMM) algorithm is put forward in this paper. The framework of the proposed algorithm is a co-ordinated convex distribution framework with inner and outer layers. The outer layer is a penalty convex–concave procedure (PCCP), the inner layer is an ADMM-FE (forced equality) procedure. In this framework, the outer layer optimization uses the convex and concave procedure to turn the non-convex airflow equation into a second-order cone constraint with successive iterations, and the inner layer ADMM-FE algorithm solves the convex model to obtain a convergent solution. In the end, we compare the established algorithm with the traditional ADMM algorithm and the centralized optimization algorithm through example simulation analysis, and the results verify the effectiveness of the proposed model and optimization algorithm framework.

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14

Towle, Eli, i James Luedtke. "Intersection Disjunctions for Reverse Convex Sets". Mathematics of Operations Research 47, nr 1 (luty 2022): 297–319. http://dx.doi.org/10.1287/moor.2021.1132.

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We present a framework to obtain valid inequalities for a reverse convex set: the set of points in a polyhedron that lie outside a given open convex set. Reverse convex sets arise in many models, including bilevel optimization and polynomial optimization. An intersection cut is a well-known valid inequality for a reverse convex set that is generated from a basic solution that lies within the convex set. We introduce a framework for deriving valid inequalities for the reverse convex set from basic solutions that lie outside the convex set. We first propose an extension to intersection cuts that defines a two-term disjunction for a reverse convex set, which we refer to as an intersection disjunction. Next, we generalize this analysis to a multiterm disjunction by considering the convex set’s recession directions. These disjunctions can be used in a cut-generating linear program to obtain valid inequalities for the reverse convex set.

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15

Flamant, Julien, Sebastian Miron i David Brie. "A General Framework for Constrained Convex Quaternion Optimization". IEEE Transactions on Signal Processing 70 (2022): 254–67. http://dx.doi.org/10.1109/tsp.2021.3137746.

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16

Ho-Nguyen, Nam, i Fatma Kılınç-Karzan. "Online First-Order Framework for Robust Convex Optimization". Operations Research 66, nr 6 (listopad 2018): 1670–92. http://dx.doi.org/10.1287/opre.2018.1764.

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17

Bertsekas, Dimitri P., i Huizhen Yu. "A Unifying Polyhedral Approximation Framework for Convex Optimization". SIAM Journal on Optimization 21, nr 1 (styczeń 2011): 333–60. http://dx.doi.org/10.1137/090772204.

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18

Eichfelder, Gabriele, i Patrick Groetzner. "A note on completely positive relaxations of quadratic problems in a multiobjective framework". Journal of Global Optimization 82, nr 3 (15.10.2021): 615–26. http://dx.doi.org/10.1007/s10898-021-01091-2.

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AbstractIn a single-objective setting, nonconvex quadratic problems can equivalently be reformulated as convex problems over the cone of completely positive matrices. In small dimensions this cone equals the cone of matrices which are entrywise nonnegative and positive semidefinite, so the convex reformulation can be solved via SDP solvers. Considering multiobjective nonconvex quadratic problems, naturally the question arises, whether the advantage of convex reformulations extends to the multicriteria framework. In this note, we show that this approach only finds the supported nondominated points, which can already be found by using the weighted sum scalarization of the multiobjective quadratic problem, i.e. it is not suitable for multiobjective nonconvex problems.

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19

Tran-Dinh, Quoc, Ling Liang i Kim-Chuan Toh. "A New Homotopy Proximal Variable-Metric Framework for Composite Convex Minimization". Mathematics of Operations Research 47, nr 1 (luty 2022): 508–39. http://dx.doi.org/10.1287/moor.2021.1138.

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This paper suggests two novel ideas to develop new proximal variable-metric methods for solving a class of composite convex optimization problems. The first idea is to utilize a new parameterization strategy of the optimality condition to design a class of homotopy proximal variable-metric algorithms that can achieve linear convergence and finite global iteration-complexity bounds. We identify at least three subclasses of convex problems in which our approach can apply to achieve linear convergence rates. The second idea is a new primal-dual-primal framework for implementing proximal Newton methods that has attractive computational features for a subclass of nonsmooth composite convex minimization problems. We specialize the proposed algorithm to solve a covariance estimation problem in order to demonstrate its computational advantages. Numerical experiments on the four concrete applications are given to illustrate the theoretical and computational advances of the new methods compared with other state-of-the-art algorithms.

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20

Xu, Hui, Yongguo Yang, Xin Wang, Mingming Liu, Hongxia Xie i Chujiao Wang. "Multiple Kernel Dimensionality Reduction via Ratio-Trace and Marginal Fisher Analysis". Mathematical Problems in Engineering 2019 (14.01.2019): 1–8. http://dx.doi.org/10.1155/2019/6941475.

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Traditional supervised multiple kernel learning (MKL) for dimensionality reduction is generally an extension of kernel discriminant analysis (KDA), which has some restrictive assumptions. In addition, they generally are based on graph embedding framework. A more general multiple kernel-based dimensionality reduction algorithm, called multiple kernel marginal Fisher analysis (MKL-MFA), is presented for supervised nonlinear dimensionality reduction combined with ratio-race optimization problem. MKL-MFA aims at relaxing the restrictive assumption that the data of each class is of a Gaussian distribution and finding an appropriate convex combination of several base kernels. To improve the efficiency of multiple kernel dimensionality reduction, the spectral regression frameworks are incorporated into the optimization model. Furthermore, the optimal weights of predefined base kernels can be obtained by solving a different convex optimization. Experimental results on benchmark datasets demonstrate that MKL-MFA outperforms the state-of-the-art supervised multiple kernel dimensionality reduction methods.

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21

Chen, J. "A theoretical framework of regional cone-beam tomography". IEEE Transactions on Medical Imaging 11, nr 3 (1992): 342–50. http://dx.doi.org/10.1109/42.158938.

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22

Benson, T. M., i J. Gregor. "Framework for iterative cone-beam micro-CT reconstruction". IEEE Transactions on Nuclear Science 52, nr 5 (październik 2005): 1335–40. http://dx.doi.org/10.1109/tns.2005.858206.

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23

Khan, L. A., i A. B. Thaheem. "Multiplication operators on weighted spaces in the non-locally convex framework". International Journal of Mathematics and Mathematical Sciences 20, nr 1 (1997): 75–79. http://dx.doi.org/10.1155/s0161171297000112.

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LetXbe a completely regular Hausdorff space,Ea topological vector space,Va Nachbin family of weights onX, andCV0(X,E)the weighted space of continuousE-valued functions onX. Letθ:X→Cbe a mapping,f∈CV0(X,E)and defineMθ(f)=θf(pointwise). In caseEis a topological algebra,ψ:X→Eis a mapping then defineMψ(f)=ψf(pointwise). The main purpose of this paper is to give necessary and sufficient conditions forMθandMψto be the multiplication operators onCV0(X,E)whereEis a general topological space (or a suitable topological algebra) which is not necessarily locally convex. These results generalize recent work of Singh and Manhas based on the assumption thatEis locally convex.

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24

Vrankic, Ilko, i Mira Krpan. "Short Run Profit Maximization in a Convex Analysis Framework". Interdisciplinary Description of Complex Systems 15, nr 1 (2017): 1–15. http://dx.doi.org/10.7906/indecs.15.1.1.

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Sun, Churen. "Robust convex conic optimization in D-induced duality framework". Journal of Information and Optimization Sciences 29, nr 4 (lipiec 2008): 603–30. http://dx.doi.org/10.1080/02522667.2008.10699824.

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Rostampour, Vahab, i Tamás Keviczky. "Distributed Computational Framework for Large-Scale Stochastic Convex Optimization". Energies 14, nr 1 (23.12.2020): 23. http://dx.doi.org/10.3390/en14010023.

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This paper presents a distributed computational framework for stochastic convex optimization problems using the so-called scenario approach. Such a problem arises, for example, in a large-scale network of interconnected linear systems with local and common uncertainties. Due to the large number of required scenarios to approximate the stochasticity of these problems, the stochastic optimization involves formulating a large-scale scenario program, which is in general computationally demanding. We present two novel ideas in this paper to address this issue. We first develop a technique to decompose the large-scale scenario program into distributed scenario programs that exchange a certain number of scenarios with each other to compute local decisions using the alternating direction method of multipliers (ADMM). We show the exactness of the decomposition with a-priori probabilistic guarantees for the desired level of constraint fulfillment for both local and common uncertainty sources. As our second contribution, we develop a so-called soft communication scheme based on a set parametrization technique together with the notion of probabilistically reliable sets to reduce the required communication between the subproblems. We show how to incorporate the probabilistic reliability notion into existing results and provide new guarantees for the desired level of constraint violations. Two different simulation studies of two types of interconnected network, namely dynamically coupled and coupling constraints, are presented to illustrate advantages of the proposed distributed framework.

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27

Tran-Dinh, Quoc, Ahmet Alacaoglu, Olivier Fercoq i Volkan Cevher. "An adaptive primal-dual framework for nonsmooth convex minimization". Mathematical Programming Computation 12, nr 3 (31.10.2019): 451–91. http://dx.doi.org/10.1007/s12532-019-00173-3.

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Bonami, Pierre, Lorenz T. Biegler, Andrew R. Conn, Gérard Cornuéjols, Ignacio E. Grossmann, Carl D. Laird, Jon Lee i in. "An algorithmic framework for convex mixed integer nonlinear programs". Discrete Optimization 5, nr 2 (maj 2008): 186–204. http://dx.doi.org/10.1016/j.disopt.2006.10.011.

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Fokkink, Wan, Jun Pang i Jaco van de Pol. "Cones and foci: A mechanical framework for protocol verification". Formal Methods in System Design 29, nr 1 (9.06.2006): 1–31. http://dx.doi.org/10.1007/s10703-006-0004-3.

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Georgescu, Flavian. "Iterated Function Systems Consisting of Generalized Convex Contractions in the Framework of Complete Strong b-metric Spaces". Annals of West University of Timisoara - Mathematics and Computer Science 55, nr 2 (1.12.2017): 119–42. http://dx.doi.org/10.1515/awutm-2017-0018.

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AbstractThe concept of generalized convex contraction was introduced and studied by V. Istrăţescu and the notion ofb-metric space was introduced by I. A. Bakhtin and S. Czerwik. In this paper we combine these two elements by studying iterated function systems consisting of generalized convex contractions on the framework ofb-metric spaces. More precisely we prove the existence and uniqueness of the attractor of such a system providing in this way a generalization of Istrăţescu’s convex contractions fixed point theorem in the setting of complete strongb-metric spaces.

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Nazemi, Alireza. "A new collaborate neuro-dynamic framework for solving convex second order cone programming problems with an application in multi-fingered robotic hands". Applied Intelligence 49, nr 10 (15.04.2019): 3512–23. http://dx.doi.org/10.1007/s10489-019-01462-z.

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Eraslan, Oguz, Ozgur Inan i Asli Secilmis. "The Effect of Framework Design on Stress Distribution in Implant-Supported FPDs: A 3-D FEM Study". European Journal of Dentistry 04, nr 04 (październik 2010): 374–82. http://dx.doi.org/10.1055/s-0039-1697856.

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Objectives: The biomechanical behavior of the superstructure plays an important role in the functional longevity of dental implants. However, information about the influence of framework design on stresses transmitted to the implants and supporting tissues is limited. The purpose of this study was to evaluate the effects of framework designs on stress distribution at the supporting bone and supporting implants.Methods: In this study, the three-dimensional (3D) finite element stress analysis method was used. Three types of 3D mathematical models simulating three different framework designs for implant- supported 3-unit posterior fixed partial dentures were prepared with supporting structures. Convex (1), concave (2), and conventional (3) pontic framework designs were simulated. A 300-N static vertical occlusal load was applied on the node at the center of occlusal surface of the pontic to calculate the stress distributions. As a second condition, frameworks were directly loaded to evaluate the effect of the framework design clearly. The Solidworks/Cosmosworks structural analysis programs were used for finite element modeling/analysis.Results: The analysis of the von Mises stress values revealed that maximum stress concentrations were located at the loading areas for all models. The pontic side marginal edges of restorations and the necks of implants were other stress concentration regions. There was no clear difference among models when the restorations were loaded at occlusal surfaces. When the veneering porcelain was removed, and load was applied directly to the framework, there was a clear increase in stress concentration with a concave design on supporting implants and bone structure.Conclusions: The present study showed that the use of a concave design in the pontic frameworks of fixed partial dentures increases the von Mises stress levels on implant abutments and supporting bone structure. However, the veneering porcelain element reduces the effect of the framework and compensates for design weaknesses. (Eur J Dent 2010;4:374-382)

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Adeyemi, T. A., F. Akusah, A. A. Mebawondu, M. O. Adewole i O. K. Narain. "THE EXISTENCE OF A SOLUTION OF THE NONLINEAR INTEGRAL EQUATION VIA THE FIXED POINT APPROACH". Advances in Mathematics: Scientific Journal 10, nr 7 (19.07.2021): 2977–98. http://dx.doi.org/10.37418/amsj.10.7.5.

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In this paper, we present some fixed point results for a generalized class of nonexpansive mappings in the framework of uniformly convex hyperbolic space and also propose a new iterative scheme for approximating the fixed point of this class of mappings in the framework of uniformly convex hyperbolic spaces. Furthermore, we establish some basic properties and some strong and $\triangle$-convergence theorems for these mappings in uniformly convex hyperbolic spaces. Finally, we present an application to the nonlinear integral equation and also, a numerical example to illustrate our main result and then display the efficiency of the proposed algorithm compared to different iterative algorithms in the literature with different choices of parameters and initial guesses. The results obtained in this paper extends and generalizes corresponding results in uniformly convex Banach spaces, CAT(0) spaces and other related results in literature.

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Tri Maryana, Okky Fajar, L. Y. Ginting, F. Pahlawan i M. Y. Darmawan. "Eksperimen Gangguan Getaran Pada Fenomena Cloaking Cahaya Tampak Sistem Empat Lensa". Journal of Science and Applicative Technology 3, nr 2 (31.12.2019): 55. http://dx.doi.org/10.35472/jsat.v3i2.213.

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Creating optical illusions or invisible objects by using cloaking devices is still being a concern for many researchers in the world. The cloaking devices are working in visible spectrum regime, large dimention, and replicable. Addition with the full-field of light, no new materials, simple infrastructure, and scale easily may be considered an ‘ideal’ cloaking device. Based on four lenses cloaking system by Choi’s work shows an idea for solution of blindspot large vehicle’s problem. The set up for this optical system is regular covex lenses non-aberation based on educational laboratory framework. The experimental confirmation that cloaking area with 4f convex lenses is limited to certain areas only, not 100 % of the object to be observed can disappear from the view. Vibration disturbance generated by rotor module (wheels disturbance analogy on vehicles) applied on the system demonstrate that below on 2000 rotation per minutes (rpm) equal 33.34 hertz, optical illusion is still consistent. The results support the information to create optical cloaking prototype for optimizing large vehicle driver’s visibility as alternative solution blindspot’s problem.

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Penot, Jean-Paul. "Autoconjugate functions and representations of monotone operators". Bulletin of the Australian Mathematical Society 67, nr 2 (kwiecień 2003): 277–84. http://dx.doi.org/10.1017/s0004972700033748.

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We show the existence of a convex representation of a maximal monotone operator by a convex function which is invariant with respect to the Fenchel conjugacy (up to an interchange of variables). We use the framework of generalized convexity.

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Prakasvudhisarn, Chakguy, i Shivakumar Raman. "Framework for Cone Feature Measurement Using Coordinate Measuring Machines". Journal of Manufacturing Science and Engineering 126, nr 1 (1.02.2004): 169–77. http://dx.doi.org/10.1115/1.1644541.

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Complex forms such as conicity have been largely ignored in the coordinate form literature, in spite of the sufficient need to inspect them in parts such as tapered rollers in bearings. This paper attempts to develop guidelines for inspection of cones and conical frustums using probe-type coordinate measuring machines. The sampling problem, the path determination, and fitting of form zones are each addressed in detail. Moreover, an integrative approach is taken for form verification and detailed experimental analysis is conducted as a pilot study for demonstrating the need for the same. Three separate sampling methods are applied: Hammersley, Halton-Zaremba, and Aligned Systematic; at various sample sizes using sampling theory and prior work in two-dimensional sampling. Linear and nonlinear deviations are formulated using optimization and least-squared methods and solved to yield competitive solutions. Comprehensive experimental analysis investigated issues of model adequacy, nesting, interactions, and individual effects, while studying conicity as a response variable in the light of sampling strategies, sizes, cone surface areas, and fitting methods. In summary, an orderly framework for sampling and fitting cones is developed which can lead to the development of comprehensive standards and solutions for industry.

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Ge Wang i Shiying Zhao. "Feldkamp-type cone-beam tomography in the wavelet framework". IEEE Transactions on Medical Imaging 19, nr 9 (2000): 922–29. http://dx.doi.org/10.1109/42.887839.

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Zhao, Shiying, Hengyong Yu i Ge Wang. "A unified framework for exact cone-beam reconstruction formulas". Medical Physics 32, nr 6Part1 (25.05.2005): 1712–21. http://dx.doi.org/10.1118/1.1869632.

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Elliott, Robert J., Tak Kuen Siu i Samuel N. Cohen. "Backward stochastic difference equations for dynamic convex risk measures on a binomial tree". Journal of Applied Probability 52, nr 3 (wrzesień 2015): 771–85. http://dx.doi.org/10.1239/jap/1445543845.

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Using backward stochastic difference equations (BSDEs), this paper studies dynamic convex risk measures for risky positions in a simple discrete-time, binomial tree model. A relationship between BSDEs and dynamic convex risk measures is developed using nonlinear expectations. The time consistency of dynamic convex risk measures is discussed in the binomial tree framework. A relationship between prices and risks is also established. Two particular cases of dynamic convex risk measures, namely risk measures with stochastic distortions and entropic risk measures, and their mathematical properties are discussed.

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40

Elliott, Robert J., Tak Kuen Siu i Samuel N. Cohen. "Backward stochastic difference equations for dynamic convex risk measures on a binomial tree". Journal of Applied Probability 52, nr 03 (wrzesień 2015): 771–85. http://dx.doi.org/10.1017/s0021900200113427.

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Using backward stochastic difference equations (BSDEs), this paper studies dynamic convex risk measures for risky positions in a simple discrete-time, binomial tree model. A relationship between BSDEs and dynamic convex risk measures is developed using nonlinear expectations. The time consistency of dynamic convex risk measures is discussed in the binomial tree framework. A relationship between prices and risks is also established. Two particular cases of dynamic convex risk measures, namely risk measures with stochastic distortions and entropic risk measures, and their mathematical properties are discussed.

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41

Al-Sulaiman, Talal, i Ali Al-Matouq. "A Convex Collaborative Filtering Framework for Global Market Return Prediction". IEEE Access 9 (2021): 29458–69. http://dx.doi.org/10.1109/access.2021.3058646.

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Bolívar-Nieto, Edgar A., Tyler Summers, Robert D. Gregg i Siavash Rezazadeh. "A convex optimization framework for robust-feasible series elastic actuators". Mechatronics 79 (listopad 2021): 102635. http://dx.doi.org/10.1016/j.mechatronics.2021.102635.

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Burger, Mathias, Giuseppe Notarstefano i Frank Allgower. "A Polyhedral Approximation Framework for Convex and Robust Distributed Optimization". IEEE Transactions on Automatic Control 59, nr 2 (luty 2014): 384–95. http://dx.doi.org/10.1109/tac.2013.2281883.

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Maehara, Takanori, i Kazuo Murota. "A framework of discrete DC programming by discrete convex analysis". Mathematical Programming 152, nr 1-2 (2.07.2014): 435–66. http://dx.doi.org/10.1007/s10107-014-0792-y.

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Mazumder, Rahul, Arkopal Choudhury, Garud Iyengar i Bodhisattva Sen. "A Computational Framework for Multivariate Convex Regression and Its Variants". Journal of the American Statistical Association 114, nr 525 (15.08.2018): 318–31. http://dx.doi.org/10.1080/01621459.2017.1407771.

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Guzman, Yannis A., M. M. Faruque Hasan i Christodoulos A. Floudas. "Performance of convex underestimators in a branch-and-bound framework". Optimization Letters 10, nr 2 (23.09.2014): 283–308. http://dx.doi.org/10.1007/s11590-014-0799-6.

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Aguirre-Hernández, Baltazar, Faustino Ricardo García-Sosa, Carlos Arturo Loredo-Villalobos, Raúl Villafuerte-Segura i Eric Campos-Cantón. "Open Problems Related to the Hurwitz Stability of Polynomials Segments". Mathematical Problems in Engineering 2018 (2018): 1–8. http://dx.doi.org/10.1155/2018/2075903.

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In the framework of robust stability analysis of linear systems, the development of techniques and methods that help to obtain necessary and sufficient conditions to determine stability of convex combinations of polynomials is paramount. In this paper, knowing that Hurwitz polynomials set is not a convex set, a brief overview of some results and open problems concerning the stability of the convex combinations of Hurwitz polynomials is then provided.

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Sigauke, Caston, Murendeni Nemukula i Daniel Maposa. "Probabilistic Hourly Load Forecasting Using Additive Quantile Regression Models". Energies 11, nr 9 (23.08.2018): 2208. http://dx.doi.org/10.3390/en11092208.

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Short-term hourly load forecasting in South Africa using additive quantile regression (AQR) models is discussed in this study. The modelling approach allows for easy interpretability and accounting for residual autocorrelation in the joint modelling of hourly electricity data. A comparative analysis is done using generalised additive models (GAMs). In both modelling frameworks, variable selection is done using least absolute shrinkage and selection operator (Lasso) via hierarchical interactions. Four models considered are GAMs and AQR models with and without interactions, respectively. The AQR model with pairwise interactions was found to be the best fitting model. The forecasts from the four models were then combined using an algorithm based on the pinball loss (convex combination model) and also using quantile regression averaging (QRA). The AQR model with interactions was then compared with the convex combination and QRA models and the QRA model gave the most accurate forecasts. Except for the AQR model with interactions, the other two models (convex combination model and QRA model) gave prediction interval coverage probabilities that were valid for the 90 % , 95 % and the 99 % prediction intervals. The QRA model had the smallest prediction interval normalised average width and prediction interval normalised average deviation. The modelling framework discussed in this paper has established that going beyond summary performance statistics in forecasting has merit as it gives more insight into the developed forecasting models.

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Nazemi, Alireza, i Atiye Sabeghi. "A new neural network framework for solving convex second-order cone constrained variational inequality problems with an application in multi-finger robot hands". Journal of Experimental & Theoretical Artificial Intelligence 32, nr 2 (12.08.2019): 181–203. http://dx.doi.org/10.1080/0952813x.2019.1647559.

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Dhiman, Gaurav, Sen Guo i Satnam Kaur. "ED-SHO: A framework for solving nonlinear economic load power dispatch problem using spotted hyena optimizer". Modern Physics Letters A 33, nr 40 (28.12.2018): 1850239. http://dx.doi.org/10.1142/s0217732318502395.

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This paper presents the application of recently developed metaheuristic optimization algorithm, the spotted hyena optimizer, for solving both convex and non-convex economic dispatch problems. The proposed algorithm has been tested on various test systems (i.e. 6, 10, 20, and 40 generators systems) and compared with other well-known approaches to demonstrate its effectiveness and efficiency. The results show that the proposed algorithm is able to solve economic load power dispatch problem and converge toward the optimum with low computational efforts.

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