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International Joint Conference on Neural Networks (IJCNN)

作者： M.A. Teixeira G. Zaverucha Systems Engineering and Computer Science-COPPE Federal University of Rio de Janeiro Rio de Janeiro Brazil

We present three different approaches for multi-step prediction using the fuzzy Markov predictor (FMP). The FMP is a modification of the hidden Markov model in order to enable it to predict numerical values. In the first approach, the one normally used in neural networks, past predictions are used as input for the next predictions. The second and third approaches follow the standard way of making multi-step prediction in a dynamic Bayesian network. FMP using these three approaches is applied to the task of monthly electric load multi-step forecasting and successfully compared with two Kalman filter models, BATS and STAMP, and two traditional forecasting methods, Box-Jenkins and Winters exponential smoothing.

关键词： Load forecasting Hidden Markov models Predictive models Multidimensional systems Machine learning Power engineering and energy systems engineering and theory computer science Neural networks Bayesian methods

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Evaluating the DSMIO cache-coherence algorithm in cluster-based parallel ODBMS 8th

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8th International Conference on Object-Oriented Information systems, OOIS 2002

作者： Osthoff, Carla Bentes, Cristiana Ariosto, Daniel Mattoso, Marta Amorim, Claudio L. Computer Science Department LNCC Spain Systems Engineering Department UERJ Spain Computer Science Department COPPE/UFRJ Spain

ISBN: (纸本)3540440879

In this paper, we assess the performance of DSMIO cachecoherence algorithm implemented in a parallel object-based database management system (ODBMS). The distinguishing feature of DSMIO is its use of the lazy release memory consistency model and multiplewriter protocol to reduce both the number and size of coherence messages required to keep coherent a distributed ODBMS across a cluster of PC servers. Using a large distributed database and several application workloads we evaluate DSMIO performance and also compare it against that of the well-known Call-Back Locking (CBL) algorithm. Our results showt hat both algorithms perform very well for read operations whereas DSMIO outperforms significantly CBL for write operations with DSMIO speed-ups attaining as much as 5.4 while CBL speed-ups reach at most 1.4 for an 8-node cluster. Overall, these results suggest that designers of cluster-based ODBMS should consider D. © Springer-Verlag Berlin Heidelberg 2002

关键词： Locks (fasteners)

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Fuzzy Markov predictor with first and second-order dependences

Fuzzy Markov predictor with first and second-order dependenc...

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Brazilian Symposium on Neural Networks

作者： M.A. Teixeira G. Zaverucha Systems Engineering and Computer Science-COPPE Federal University of Rio de Janeiro Brazil

We present two new versions of the fuzzy Markov predictor (FMP) with different dependences among the inputs: first-order and second-order dependences. The FMP is a modification of the hidden Markov model in order to enable it to predict numerical values. The FMP can be seen as an extension of the fuzzy Bayes predictor. These hybrid systems are applied to the task of monthly electric load forecasting and successfully compared with one fuzzy system, and two traditional forecasting methods: Box-Jenkins and Winters exponential smoothing.

关键词： Fuzzy systems Hidden Markov models Load forecasting Niobium compounds Smoothing methods Shape Fuzzy neural networks Power engineering and energy systems engineering and theory computer science

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Fuzzy Markov predictor in electric load forecasting

Fuzzy Markov predictor in electric load forecasting

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International Joint Conference on Neural Networks (IJCNN)

作者： M.A. Teixeira G. Zaverucha Systems Engineering and Computer Science Program Federal University of Rio de Janeiro Brazil Systems Engineering and Computer Science Program E28093 Graduate Programs in Engineering (COPPE) Federal University of Rio de Janeiro Brazil

We present the fuzzy Markov predictor (FMP), a hybrid system that is applied to the task of monthly electric load forecasting. The FMP is a modification we introduce in the hidden Markov model in order to enable it to predict numerical values. The FMP can be seen as an extension of the fuzzy Bayes predictor (FBP) that was modified from the naive Bayes classifier. For verifying the efficiency of the FMP's prediction, we compare it with the FBP, one fuzzy system and two traditional forecasting methods, Box-Jenkins and Winters exponential smoothing.

关键词： Load forecasting Fuzzy systems Hidden Markov models Power engineering and energy Smoothing methods Niobium compounds systems engineering and theory computer science Predictive models Electric variables measurement

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Efficient categorization of memory sharing patterns in software DSM systems 15

Efficient categorization of memory sharing patterns in softw...

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15th International Parallel and Distributed Processing Symposium, IPDPS 2001

作者： De Castro, M.C.S. De Amorim, C.L. Computer Science Department Federal University of Juiz de Fora Minas Gerais Brazil COPPE - Systems Engineering Federal University of Rio de Janeiro Rio de Janeiro Brazil

ISBN: (纸本)0769509908

This work introduces a new technique that enables SDSMs to categorize dynamically and accurately memory sharing patterns in both classes of regular and irregular applications. The categorization is carried out automatically at run-time on a per-page basis, requiring no user or compiler assistance. We evaluate the potential benefits of our technique using execution-driven simulations of 8 applications running on TrendMarks on a network of 8 workstations. Surprisingly, we found that producer-consumer(s) and migratory are the dominant patterns even in irregular applications. Preliminary results suggest that the categorization technique we propose is a promising option to further improve the performance of current adaptive SDSM systems. © 2001 IEEE.

关键词： adaptive software DSM systems latency-hiding techniques memory sharing patterns

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Fuzzy Bayes predictor in electric load forecasting

Fuzzy Bayes predictor in electric load forecasting

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International Joint Conference on Neural Networks (IJCNN)

作者： M.A. Teixeira G. Zaverucha V.N.A.L. da Silva G.F. Ribeiro Systems Engineering and Computer Science Program Graduate Programs in Engineering COPPE Federal University of Rio de Janeiro Brazil Electric Power Research Center CEPEL CEPEL Brazil

ISBN: (纸本)0780370449

We present the fuzzy Bayes predictor (FBP), a hybrid system for the task of monthly electric load forecasting. The FBP is a modification we introduce in the naive Bayes classifier in order to enable it to predict numerical values. We consider three versions of the FBP, each one with a different dependence among the input data: independence, first-order and second-order dependence. For verifying the efficiency of the FBP's prediction, we compare it with two fuzzy systems and two traditional forecasting methods, Box-Jenkins and Winters exponential smoothing.

关键词： Load forecasting Fuzzy systems Power engineering and energy Smoothing methods Testing Niobium compounds systems engineering and theory computer science Predictive models Electric variables measurement

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Hyperbolic Penalty: A New Method for Nonlinear Programming with Inequalities

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International Transactions in Operational Research 2001年第6期8卷 659-671页

作者： Xavier, Adilson Elias Department of Systems Engineering and Computer Science Graduate School of Engineering (COPPE) Federal University of Rio de Janeiro Rio de Janeiro RJ 21945-970 Brazil

This work intends to present and to analyze a new penalty method that purposes to solve the general nonlinear programming problem subject to inequality constraints. The proposed method has the important feature of being completely differentiable and combines features of both exterior and interior penalty methods. Numerical results for some problems are commented on. International Federation of Operational Research Societies 2001.

关键词： Nonlinear programming Penalty methods

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Efficient categorization of memory sharing patterns in software DSM systems

Efficient categorization of memory sharing patterns in softw...

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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： M.C.S. de Castro C.L. de Amorim Computer Science Department Federal University of Juiz de Fora Minas Gerais Brazil COPPE-Systems Engineering Federal University of Rio de Janeiro Rio de Janeiro Brazil

ISBN: (纸本)0769509908

关键词： Software systems Workstations Adaptive systems Prefetching Access protocols computer science systems engineering and theory Runtime Modeling Application software

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A boundary extraction method based on Dual-T-Snakes and dynamic programming

A boundary extraction method based on Dual-T-Snakes and dyna...

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： G.A. Giraldi E. Strauss A.A. Oliveira COPPE Systems Engineering and Computer Science Brazil

The original proposal of active contour models, also called snakes, for image segmentation, suffers from a strong sensitivity to its initial position and can not deal with topological changes. The sensitivity to initialization can be addressed by dynamic programming (DP) techniques which have the advantage of guaranteeing the global minimum and of being more stable numerically than the variational approaches. Their disadvantages are the storage requirements and computational complexity. In this paper we address these limitations of DP by reducing the region of interest (search space) through the use of the Dual-T-Snake approach. The solution of this method consists of two curves enclosing each object boundary which allows the definition of a more efficient search space for a DP technique. The resulting method (Dual-T-Snake plus DP) inherits the capability of changing the topology and avoiding local minima from the Dual-T-Snake and the global optimal properties of the dynamic programming. It can be also extended for 3D.

关键词： Dynamic programming Image segmentation Electrical capacitance tomography computer graphics Laboratories systems engineering and theory computer science Postal services Proposals Active contours

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The impact of cache coherence protocols on parallel logic programming systems 1

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1st International Conference on Computational Logic, CL 2000

作者： De Castro Dutra, Inês Costa, Vítor Santos Bianchini, Ricardo COPPE Systems Engineering Federal University of Rio de Janeiro Rio de Janeiro 21945-970 Brazil Department of Computer Science Rutgers University Piscataway NJ 08854-8019 United States

ISBN: (数字)9783540449577

ISBN: (纸本)3540677976

In this paper we use execution-driven simulation of a scalable multiprocessor to evaluate the performance of the Andorra-I parallel logic programming system under invalidate and update-based protocols. We use two versions of Andorra-I. One of them was originally designed for bus-based multiprocessors, while the other is optimised for scalable architectures. We study a well-known invalidate protocol and two different update-based protocols. Our results show that for our sample logic programs the update-based protocols outperform their invalidate-based counterpart for the original version of Andorra-I. In contrast, the optimised version of Andorra-I benefits the most from the invalidate-based protocol, but a hybrid update-based protocol performs as well as the invalidate protocol in most cases. We conclude that parallel logic programming systems can consistently benefit from hybrid update-based protocols. © Springer-Verlag Berlin Heidelberg 2000.

关键词： computer circuits

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