Indexing Temporal Information for Web Pages
Peiquan Jin, Hong Chen, Xujian Zhao, Xiaowen Li, Lihua Yue (2011)
Computer Science and Information Systems
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Peiquan Jin, Hong Chen, Xujian Zhao, Xiaowen Li, Lihua Yue (2011)
Computer Science and Information Systems
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Chiş, Monica (2002)
Acta Universitatis Apulensis. Mathematics - Informatics
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Przemysław Grudziński, Marek Wojciechowski (2009)
Control and Cybernetics
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R. S. Bucy, R. S. Diesposti (1993)
ESAIM: Mathematical Modelling and Numerical Analysis - Modélisation Mathématique et Analyse Numérique
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Kristína Machová, Miroslav Puszta, František Barčák, Peter Bednár (2006)
Computer Science and Information Systems
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Yunfeng He, Junqing Yu (2010)
Computer Science and Information Systems
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Wojciech Jaśkowski, Krzysztof Krawiec, Bartosz Wieloch (2014)
International Journal of Applied Mathematics and Computer Science
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Hervé Kerivin, Mathieu Lacroix, Alain Quilliot, Hélène Toussaint (2011)
RAIRO - Operations Research
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In this paper we deal with the preemptive asymmetric stacker crane problem in a heuristic way. We first present some theoretical results which allow us to turn this problem into a specific tree design problem. We next derive from this new representation an integer linear programming model together with simple and efficient greedy and local search heuristics. We conclude by presenting experimental results which aim at both testing the efficiency of our heuristic and evaluating the impact...
Hervé Kerivin, Mathieu Lacroix, Alain Quilliot, Hélène Toussaint (2011)
RAIRO - Operations Research
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In this paper we deal with the preemptive asymmetric stacker crane problem in a heuristic way. We first present some theoretical results which allow us to turn this problem into a specific tree design problem. We next derive from this new representation an integer linear programming model together with simple and efficient greedy and local search heuristics. We conclude by presenting experimental results which aim at both testing the efficiency of our heuristic and evaluating the impact...
Rafał Biedrzycki, Jarosław Arabas (2012)
International Journal of Applied Mathematics and Computer Science
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This paper presents an application of methods from the machine learning domain to solving the task of DNA sequence recognition. We present an algorithm that learns to recognize groups of DNA sequences sharing common features such as sequence functionality. We demonstrate application of the algorithm to find splice sites, i.e., to properly detect donor and acceptor sequences. We compare the results with those of reference methods that have been designed and tuned to detect splice sites....