This paper presents the development of an algorithm to multipartition an observable power system state estimation (PSSE) network into two or more observable subnetworks. The partitioning algorithm is based on using th...
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This paper presents the development of an algorithm to multipartition an observable power system state estimation (PSSE) network into two or more observable subnetworks. The partitioning algorithm is based on using the simulated annealing principle which has a theoretical basis in combinatorial optimization, rather than a heuristic derivation. Computational examples, using several power networks, are given to illustrate the properties of the proposed algorithm.
The partitioning approach essentially constitutes an adaptive framework which is a unifying and powerful setting for optimal linear and nonlinear estimation. In particular, for the class of linear estimation problems,...
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The partitioning approach essentially constitutes an adaptive framework which is a unifying and powerful setting for optimal linear and nonlinear estimation. In particular, for the class of linear estimation problems, model partitioning has yielded [Lainiotis (1971–1979) and Lainiotis and Andrisani (1979, 1983)] two novel and practically useful estimation algorithms. The first algorithm results by partitioning the initial state vector into the sum of two independent random vectors, arbitrarily chosen by the filter designer. Similarly, the second algorithm results by partitioning both the initial state, and the process-noise vectors, respectively, into the sum of two random vectors. These algorithms were shown to posses several computational advantages, and interesting properties. In this paper, based on the above results, a new linear estimation algorithm is obtained. This constitutes a per-sample partitioning version of the above Lainiotis-Andrisani algorithm. Moreover, a computational analysis of the new algorithm is made with respect to computer time and storage requirements. This is compared to the computational requirements of the Kalman filter, and relevant conclusions are drawn. Finally, to demonstrate the practical usefulness of the new algorithm to signal processing, they are applied to the important class of multi-sensor estimation problems, encountered in geophysical data processing, multi-radar problems, etc. Das Verfahren der Zerlegung in Teilbereiche steckt einen Rahmen ab, in dem lineare und nichtlineare Schätzungsprobleme in einheitlicher Weise optimal gelöst werden können. Insbesondere für die Klasse der linearen Schätz-probleme hat die Zerlegung des Modells zwei neuartige und in der Praxis nützliche Schätzalgorithmen hervorgebracht [Lainiotis (1971–1979) und Lainiotis und Andrisani (1979, 1983)]. Im ersten algorithmus wird der Eingangs-Zustandsvektor zerlegt in die Summe zweier voneinander unabhängiger Zufalls vektoren, die beim Entwurf des Filters
The exhaustive testing of today's digital circuits is not possible, owing to the vast test sequences which would have to be applied. Breaking down the circuit into manageable subcircuits (partitioning) makes exhau...
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The exhaustive testing of today's digital circuits is not possible, owing to the vast test sequences which would have to be applied. Breaking down the circuit into manageable subcircuits (partitioning) makes exhaustive testing practicable. partitioning has previously been done by the designer of the circuit in rather an ad hoc manner. The paper describes an algorithm which can be used to find the partitioning points in a circuit. The algorithm is illustrated for circuits containing reconvergent and nonreconvergent fan-outs.
A partitioning algorithm based on Benders's method1is described. This algorithm makes possible the solution of a large problem in a limited computer memory. The special properties of the partial problems of the pa...
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A partitioning algorithm based on Benders's method1is described. This algorithm makes possible the solution of a large problem in a limited computer memory. The special properties of the partial problems of the partitioned problem are exploited to reduce further memory requirements and computation time. This method has been implemented on the SEL 32/55 computer of the UNERG at Charleroi in Belgium.
The purpose of this correspondence is to provide an example computer logic graph and data concerning various partitions and mappings of this graph. This information should be of particular interest to those workers wh...
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The purpose of this correspondence is to provide an example computer logic graph and data concerning various partitions and mappings of this graph. This information should be of particular interest to those workers who are developing partitioning and mapping algorithms, since it provides a means to test and compare alternative methods. It should also be of use to those interested in other algorithms (e.g., placement, diagramming, grouping, etc.) for logic graphs.
Driven by our work on a large-scale distributed microscopic road traffic simulator, we present ENHANCE, a novel re-partitioning approach that allows incorporating fine-grained simulator-specific cost models into the p...
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Driven by our work on a large-scale distributed microscopic road traffic simulator, we present ENHANCE, a novel re-partitioning approach that allows incorporating fine-grained simulator-specific cost models into the partitioning process to account for the actual performance characteristics of the *** use of explicit cost models enables partitioning for heterogeneous resources, which are a common occurrence in cloud deployments. Importantly, ENHANCE can be used in conjunction with other partitioning approaches by further enhancing partitions according to provided cost models. We demonstrate the benefits of our approach in an experimental evaluation showing performance improvements of up to 29% against METIS under heterogeneous conditions. Taking a different perspective, the partitioning produced by ENHANCE can provide similar performance as METIS, but using up to 20% fewer resources.
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