Mesh deformation is an important element of CFD/CSD coupled time marching simulation. A mode shape-based Radial Basis Functions interpolation (M-RBF) approach is proposed to improve the efficiency of mesh deformation ...
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Mesh deformation is an important element of CFD/CSD coupled time marching simulation. A mode shape-based Radial Basis Functions interpolation (M-RBF) approach is proposed to improve the efficiency of mesh deformation in the time marching simulation. Inspired by the modal expansion theorem in vibration theory, a set of interpolation nodes is pre-selected according to the mode shapes, rather than the physical displacements at each individual time step. The data reduction scheme of the forward-backward greedy algorithm is developed to select an optimum set of interpolation nodes. The AGARD 445.6 wing, a benchmark model for transonic flutter prediction, and the Goland+ wing with a tip store, which presents complexities in both aerodynamic configuration and mode shapes, are employed to validate the accuracy, efficiency, and capability of the M-RBF approach. The results show that the optimum set of interpolation nodes can achieve the desired interpolation accuracy while having little effect on the mesh quality at all time steps. The traditional RBF mesh deformation (T-RBF) and the RBF mesh deformation method via forward greedy algorithm (G-RBF) method spent majority of CPU time on the linear system solution (approximately 99% and 77.6%, respectively) and the selection of interpolation nodes (about 87.7% and 91.9%, respectively) in the case of AGARD 445.6 and Goland+ wing. However, by eliminating the need for repeated node selections, our M-RBF approach can improve the efficiency of mesh deformation by 2 to 3 orders of magnitude compared to the T-RBF method and 1 to 2 orders of magnitude compared to the G-RBF approach. The comparison of selected interpolation nodes by the M-RBF approach to the structural grid and CFD mesh indicates that the importance of nodes on the deforming boundary may be related to their distances from the structural grid.
To improve the observation efficiency of space debris surveys, a basic sky survey observation strategy was developed, with the aim of observing more space debris based on the Wide Field Optical Telescope Array run by ...
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To improve the observation efficiency of space debris surveys, a basic sky survey observation strategy was developed, with the aim of observing more space debris based on the Wide Field Optical Telescope Array run by Shandong University. The characteristics of the telescope and dynamic changes in the movement and position of space debris are considered in this strategy. An objective function was designed based on these factors. Using the pixelated sphere method to finely divide the celestial area, applying the summation filtering method, and using a greedy algorithm, the benefit of the objective function can be maximized, thus generating the optimal sky survey observation strategy. Through simulation and observation experiments, we demonstrate that the greedy algorithm observation strategy significantly improves the number of space debris instances and the number of arc segments with respect to the conventional observation strategy. This not only improves the automation level of space debris observation tasks, but also significantly enhances the execution efficiency of telescopes for debris observation. It is very helpful for cataloging space debris and generating collision warnings.
Online learning algorithms, widely used to power search and content optimization on the web, must balance exploration and exploitation, potentially sacrificing the experience of current users in order to gain informat...
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Online learning algorithms, widely used to power search and content optimization on the web, must balance exploration and exploitation, potentially sacrificing the experience of current users in order to gain information that will lead to better decisions in the future. While necessary in the worst case, explicit exploration has a number of disadvantages compared to the greedy algorithm that always "exploits" by choosing an action that currently looks optimal. We determine under what conditions inherent diversity in the data makes explicit exploration unnecessary. We build on a recent line of work on the smoothed analysis of the greedy algorithm in the linear contextual bandits model. We improve on prior results to show that the greedy algorithm almost matches the best possible Bayesian regret rate of any other algorithm on the same problem instance whenever the diversity conditions hold. The key technical finding is that data collected by the greedy algorithm suffices to simulate a run of any other algorithm. Further, we prove that under a particular smoothness assumption, the Bayesian regret of the greedy algorithm is at most (O) over tilde (T-1/3) in the worst case, where T is the time horizon.
Track-before-detect (TBD) is an effective technique to improve detection and tracking performance for weak targets. Dynamic programming (DP) algorithm is one of the conventional TBD techniques, and has been widely app...
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Track-before-detect (TBD) is an effective technique to improve detection and tracking performance for weak targets. Dynamic programming (DP) algorithm is one of the conventional TBD techniques, and has been widely applied to weak target detection and tracking. However, in radar systems, DP-based TBD faces two main challenges: the computational burden and the complex threshold determination. greedy algorithm (GA) can avoid the above challenges and provide the same or similar performance with DP by forcing some constraints upon the related parameters. In this paper, a novel GA-based TBD (G-TBD) is proposed for weak target detection and tracking in radar systems. The proposed G-TBD contains a two-stage detection architecture. The first detection is implemented with a low threshold to eliminate many noise cells. The second detection is employed to determine whether target exists or not. Detailed analyses, including complexity, parameter settings, and detection performance, are presented. Additionally, the G-TBD is first applied to single frequency network-based MIMO passive radar in this paper. Simulations and real data confirm the effectiveness of the proposed method.
Symmetric matroids are set systems which are obtained, in some sense, by a weakening of the structure of a matroid. These set systems are characterized by a greedy algorithm and they are suitable for dealing with auto...
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Symmetric matroids are set systems which are obtained, in some sense, by a weakening of the structure of a matroid. These set systems are characterized by a greedy algorithm and they are suitable for dealing with autodual properties of matroids. Applications are given to the eulerian tours of 4-regular graphs and the theory ofg-matroids.
Partial association rules can be used for representation of knowledge, for inference in expert systems, for construction of classifiers, and for filling missing values of attributes. This paper is devoted to the study...
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Partial association rules can be used for representation of knowledge, for inference in expert systems, for construction of classifiers, and for filling missing values of attributes. This paper is devoted to the study of approximate algorithms for minimization of partial association rule length. It is shown that under some natural assumptions on the class NP, a greedy algorithm is close to the best polynomial approximate algorithms for solving of this NP-hard problem. The paper contains various bounds on precision of the greedy algorithm, bounds on minimal length of rules based on an information obtained during the greedy algorithm work, and results of theoretical and experimental study of association rules for the most part of binary information systems.
In this work, a greedy algorithm for the design of sparse linear-phase finite impulse response filters wherein the coefficients are successively fixed to zero individually is proposed. To meet the filter specification...
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In this work, a greedy algorithm for the design of sparse linear-phase finite impulse response filters wherein the coefficients are successively fixed to zero individually is proposed. To meet the filter specifications, the coefficient for which the middle value of its feasible range is closest to zero is selected to be set to zero, whereas all the other unfixed coefficients are free to change. Design examples show that the proposed technique can design FIR filters with higher sparsity than that obtained by existing nonexhaustive algorithms for given specifications. To show the optimality of the algorithm, we design 100 filters, with results showing that the global optimal solution, i.e., the sparsest solution found by exhaustive search, can be achieved in most cases, but with much less computation time.
We consider a number of density problems for integer sequences with certain divisibility properties and sequences free of arithmetic progressions. Sequences of the latter type that are generated by a computer using mo...
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We consider a number of density problems for integer sequences with certain divisibility properties and sequences free of arithmetic progressions. Sequences of the latter type that are generated by a computer using modifications of the greedy algorithm are also provided. (C) 1999 Elsevier Science B.V. All rights reserved.
The notion of matroid has been generalized to Coxeter matroid by Gelfand and Serganova. To each pair (W, P) consisting of a finite irreducible Coxeter group W and parabolic subgroup P is associated a collection of obj...
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The notion of matroid has been generalized to Coxeter matroid by Gelfand and Serganova. To each pair (W, P) consisting of a finite irreducible Coxeter group W and parabolic subgroup P is associated a collection of objects called Coxeter matroids. The (ordinary) matroids are a special case, the case W = A(n) (isomorphic to the symmetric group Sym(n+1)) and P a maximal parabolic subgroup. The main result of this paper is that for Coxeter matroids, just as for ordinary matroids, the greedy algorithm provides a solution to a naturally associated combinatorial optimization problem. Indeed, in many important cases, Coxeter matroids are characterized by this property. This result generalizes the classical Rado-Edmonds and Gale theorems. A corollary of our theorem is that, for Coxeter matroids L, the greedy algorithm solves the L-assignment problem. Let W be a finite group acting as linear transformations on a Euclidean space E, and let f(xi,eta)(w) = [w,xi, eta] for xi, eta is an element of E, w is an element of W. The L-assignment problem is to minimize the function f(xi,eta) on a given subset L subset of or equal to W. An important tool in proving the greedy result is a bijection between the set W/P of left cosets and a "concrete" collection A of tuples of subsets of a certain partially ordered set. If a pair of elements of W are related in the Bruhat order, then the corresponding elements of A are related in the Gale (greedy) order. Indeed, in many important cases, the Bruhat order on W is isomorphic to the Gale order on A. This bijection has an important implication for Coxeter matroids. It provides bases and independent sets for a Coxeter matroid, these notions not being inherent in the definition.
An approximate algorithm for minimization of weighted depth of decision trees is considered. A bound on accuracy of this algorithm is obtained which is unimprovable in general case. Under some natural assumptions on t...
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An approximate algorithm for minimization of weighted depth of decision trees is considered. A bound on accuracy of this algorithm is obtained which is unimprovable in general case. Under some natural assumptions on the class NP, the considered algorithm is close ( from the point of view of accuracy) to best polynomial approximate algorithms for minimization of weighted depth of decision trees.
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