Three algorithms for the search of oriented paths in digraphs are described, based in the generation of a tree, in which an BFS is done, in the first one, and a DFS is done, in the other two algorithms. The first one ...
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Three algorithms for the search of oriented paths in digraphs are described, based in the generation of a tree, in which an BFS is done, in the first one, and a DFS is done, in the other two algorithms. The first one is aimed at finding all the optimum paths between two vertices. The second one is aimed at solving this problem, as well as at finding the Hamiltonian paths beginning in a vertex, or at finding all the cycles of any order in the digraph. The third one is aimed at finding all the Eulerian paths or circuits. Two more algorithms, for the analysis of graph connectivity, using the same type of techniques are also described, one aimed at separating an unconnected graph into connected subgraphs, and the other aimed at searching for all existing bridges. All five algorithms are fully described and they are also implemented in a structured form, using QB as the programming language. A very compact scheme is proposed to store all the required information, using only one-dimension arrays without pointers, which allows simple programming languages to be used.
We study infinite dimensional quadratic programming problems of an integral type. The decision variable is taken in the L p space where 1 < p < infinity. In this paper the decision variable is required to have a...
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We study infinite dimensional quadratic programming problems of an integral type. The decision variable is taken in the L p space where 1 < p < infinity. In this paper the decision variable is required to have a lower bound and an upper bound on a compact interval. Two numerical algorithms are proposed for solving these problems, and the convergence properties of the proposed algorithms are given. Two numerical examples are also given to implement the proposed algorithms. (c) 2007 Elsevier B.V. All rights reserved.
An algorithm for generating three-dimensional aggregates was developed first in this study. This algorithm can model the various shapes, sizes, and angularity of coarse aggregates. The shapes, sizes, and angularity of...
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An algorithm for generating three-dimensional aggregates was developed first in this study. This algorithm can model the various shapes, sizes, and angularity of coarse aggregates. The shapes, sizes, and angularity of the generated aggregates can be correlated to those of actual aggregates. Then, algorithms were developed to model coarse aggregate gradation accurately and place the coarse aggregates randomly within the sample. Finally, algorithms were developed to generate the asphalt mastic. The triaxial compression test of the discrete-element sample of the asphalt mixture with the nominal maximum aggregate size of 16 mm was simulated to predict its dynamic modulus. The results indicate that the discrete-element model generated using the algorithms developed in this paper can predict the mixture modulus across a range of loading frequencies. DOI: 10.1061/(ASCE)CP.1943-5487.0000210. (C) 2013 American Society of Civil Engineers.
We study the problem of segmenting a sequence into k pieces so that the resulting segmentation satisfies monotonicity or unimodality constraints. Unimodal functions can be used to model phenomena in which a measured v...
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We study the problem of segmenting a sequence into k pieces so that the resulting segmentation satisfies monotonicity or unimodality constraints. Unimodal functions can be used to model phenomena in which a measured variable first increases to a certain level and then decreases. We combine a well-known unimodal regression algorithm with a simple dynamic-programming approach to obtain an optimal quadratic-time algorithm for the problem of unimodal k-segmentation. In addition, we describe a more efficient greedy-merging heuristic that is experimentally shown to give solutions very close to the optimal. As a concrete application of our algorithms, we describe methods for testing if a sequence behaves unimodally or not. The methods include segmentation error comparisons, permutation testing, and a BIC-based scoring scheme. Our experimental evaluation shows that our algorithms and the proposed unimodality tests give very intuitive results, for both real-valued and binary data.
Let G be a graph with vertex set V (G). Let n, k, d be non-negative integers such that n + 2k + d <= |V (G)| - 2 and | V (G)| - n - d are even. A matching which saturates exactly | V (G)| - d vertices is called a d...
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Let G be a graph with vertex set V (G). Let n, k, d be non-negative integers such that n + 2k + d <= |V (G)| - 2 and | V (G)| - n - d are even. A matching which saturates exactly | V (G)| - d vertices is called a defect-d matching of G. If when deleting any n vertices the remaining subgraph contains a matching of k edges and every k-matching can be extended to a defect-d matching, then G is said to be an (n, k, d)-graph. We present an algorithm to determine (0, 1, d)-graphs with d constraints. Moreover, we solve the problem of augmenting a bipartite graph G = (B, W) to be a (0, 1, d)-graph by adding fewest edges, where d = parallel to B| - |W parallel to. The latter problem is applicable to the job assignment problem, where the number of jobs does not equal the number of persons.
algorithms are presented which use a digital elevation model (DEM) to create maps of catchment areas of stream sediment sample points, and to locate optimal sample point locations. Drainage flow directions are determi...
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algorithms are presented which use a digital elevation model (DEM) to create maps of catchment areas of stream sediment sample points, and to locate optimal sample point locations. Drainage flow directions are determined by the popular "D8" algorithm, which assigns the drainage from one point on the DEM grid to one of its eight adjacent neighbors. A new "drainage enforcement" algorithm is presented that insures drainage continuity through flat areas and out of depressions. This algorithm is based on the priority-first-search weighted-graph algorithm. Relatively simple methods for defining internal basins and incorporating digitized stream data are also discussed. All of the selected methods are robust, computationally efficient, and avoid many of the problems associated with other methods. In order to support this claim, the literature is reviewed and comparisons are made between the chosen methods and other methods. A full implementation has been created, and the Pascal source-code and Win95 executable program may be downloaded from the IAMG web site. (C) 2002 Elsevier Science Ltd. All rights reserved.
A Dung argumentation framework (AF) is a pair (A,R): A is a set of abstract arguments and R subset of A x A is a binary relation, so-called the attack relation, for capturing the conflicting arguments. "Labeling&...
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A Dung argumentation framework (AF) is a pair (A,R): A is a set of abstract arguments and R subset of A x A is a binary relation, so-called the attack relation, for capturing the conflicting arguments. "Labeling" based algorithms for enumerating extensions (i.e. sets of acceptable arguments) have been set out such that arguments (i.e. elements of A) are the only subject for labeling. In this paper we present implemented algorithms for listing extensions by labeling attacks (i.e. elements of R) along with arguments. Specifically, these algorithms are concerned with enumerating all extensions of an AF under a number of argumentation semantics: preferred, stable, complete, semi stable, stage, ideal and grounded. Our algorithms have impact, in particular, on enumerating extensions of AF-extended models that allow attacks on attacks. To demonstrate this impact, we instantiate our algorithms for an example of such models: namely argumentation frameworks with recursive attacks (AFRA), thereby we end up with unified algorithms that enumerate extensions of any AF/AFRA.
We investigate the preemptive scheduling of periodic tasks with hard deadlines. We show that, even in the uniprocessor case, no pseudopolynomial-time algorithm can test the feasibility of a task system within a consta...
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We investigate the preemptive scheduling of periodic tasks with hard deadlines. We show that, even in the uniprocessor case, no pseudopolynomial-time algorithm can test the feasibility of a task system within a constant speedup bound, unless P = NP. This result contrasts with recent results for sporadic task systems. For two special cases, synchronous task systems and systems with a constant number of different task types, we provide the first polynomial-time constant-speedup feasibility tests for multiprocessor platforms. Furthermore, we show that the problem of testing feasibility is coNP-hard for synchronous multiprocessor task systems. The complexity of some of these problems has been open for a long time. We also propose a weight maximization variant of the feasibility problem, where every task has a nonnegative weight, and the goal is to find a subset of tasks that can be scheduled feasibly and has maximum weight. We give the first constant-speed, constant-approximation algorithm for the case of synchronous task systems, together with related hardness results.
algorithms for correction of the aircraft navigation information by using a satellite navigation system and an inertial navigation system are studied. The satellite system signals contain abnormal measurements of vari...
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algorithms for correction of the aircraft navigation information by using a satellite navigation system and an inertial navigation system are studied. The satellite system signals contain abnormal measurements of various durations. Improvement of the accuracy of navigation determinations is performed by filtering noise, eliminating anomalous spikes from the data, and replacing them with predicted values. It has been proposed to use the theoretically predicted value of the updated sequence in the adaptive Kalman filter in the case of detection of an anomalous measurement. In the case of the appearance of a pack of anomalous measurements, they are replaced by the predicted values obtained by using the trend and the self-organization algorithm.
algorithms are presented for density, potential temperature, conservative temperature, and the freezing temperature of seawater. The algorithms for potential temperature and density (in terms of potential temperature)...
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algorithms are presented for density, potential temperature, conservative temperature, and the freezing temperature of seawater. The algorithms for potential temperature and density (in terms of potential temperature) are updates to routines recently published by McDougall et al., while the algorithms involving conservative temperature and the freezing temperatures of seawater are new. The McDougall et al. algorithms were based on the thermodynamic potential of Feistel and Hagen;the algorithms in this study are all based on the "new extended Gibbs thermodynamic potential of seawater" of Feistel. The algorithm for the computation of density in terms of salinity, pressure, and conservative temperature produces errors in density and in the corresponding thermal expansion coefficient of the same order as errors for the density equation using potential temperature, both being twice as accurate as the International Equation of State when compared with Feistel's new equation of state. An inverse function relating potential temperature to conservative temperature is also provided. The difference between practical salinity and absolute salinity is discussed, and it is shown that the present practice of essentially ignoring the difference between these two different salinities is unlikely to cause significant errors in ocean models.
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