Results 221 to 230 of about 149,415 (266)
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Parameters and Parameter Tuning
2015Chapter 3 presented an algorithmic framework that forms the common basis for all evolutionary algorithms. A decision to use an evolutionary algorithm implies that the user adopts the main design decisions behind this framework. Thus, the main algorithm setup follows automatically: the algorithm is based on a population of candidate solutions that is ...
A. E. Eiben, J. E. Smith
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AQM Mechanism with Neuron Tuning Parameters
2020The congestion control is one of the most important questions in modern computer network performance. This article investigates the problem of adaptive neuron based choice of the Active Queue Mechanisms parameters. We evaluate the performance of the AQM mechanism in the presence of self-similar traffic based on the automatic selection of their ...
Szyguła Jakub +5 more
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NEOCOGNITRON'S PARAMETER TUNING BY GENETIC ALGORITHMS
International Journal of Neural Systems, 1999The further study on the sensitivity analysis of Neocognitron is discussed in this paper. Fukushima's Neocognitron is capable of recognizing distorted patterns as well as tolerating positional shift. Supervised learning of the Neocognitron is fulfilled by training patterns layer by layer.
Shi, D., Dong, C., Yeung, D.S.
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Tuning Of The Bison Algorithm Control Parameters
ECMS 2018 Proceedings edited by Lars Nolle, Alexandra Burger, Christoph Tholen, Jens Werner, Jens Wellhausen, 2018Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme [LO1303 (MSMT-7778/2014)]; European Regional Development Fund under the Project CEBIA-Tech [CZ.1.05/2.1.00/03.0089]; Internal Grant Agency of Tomas Bata University [IGA/CebiaTech/2018/003]; COST (European Cooperation in Science Technology ...
Kazíková, Anežka +2 more
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Adaptive tuning of SLIC parameter K
Multimedia Tools and Applications, 2021The well-known simple linear iterative clustering (SLIC) is the most effective among the existing algorithms for superpixel segmentation, which requires manual tuning of the number of superpixels K. The optimal value of the parameter K of the SLIC algorithm for a given image is yet an open issue.
Shakir Ullah, Naeem Bhatti, Muhammad Zia
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2015
In data mining, association rules can be shown when customers buy products, which products will be purchased at the same time. Scholars use this feature to develop market basket analysis to formulate marketing strategies for business. As we know, the data are changing all the time. When new data generate, the old data will be replaced. In the database,
Wei Chi Cheng +3 more
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In data mining, association rules can be shown when customers buy products, which products will be purchased at the same time. Scholars use this feature to develop market basket analysis to formulate marketing strategies for business. As we know, the data are changing all the time. When new data generate, the old data will be replaced. In the database,
Wei Chi Cheng +3 more
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2021
Regularized estimators consist of two terms, one for comparing model parameters to data and one for including prior information. The tuning parameters define the weighting: small tuning parameters emphasize the data, while large tuning parameters emphasize the prior information.
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Regularized estimators consist of two terms, one for comparing model parameters to data and one for including prior information. The tuning parameters define the weighting: small tuning parameters emphasize the data, while large tuning parameters emphasize the prior information.
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2016
Having shown that EMAS approaches are effective in solving selected benchmark and real-life problems, it would be interesting to take an insight into the exact features of the most important mechanism of EMAS, i.e. the distributed selection based on existence of non-renewable resource.
Aleksander Byrski +1 more
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Having shown that EMAS approaches are effective in solving selected benchmark and real-life problems, it would be interesting to take an insight into the exact features of the most important mechanism of EMAS, i.e. the distributed selection based on existence of non-renewable resource.
Aleksander Byrski +1 more
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Active Tuning of Intrinsic Camera Parameters
IEEE Transactions on Automation Science and Engineering, 2009In the last years, the research effort of the scientific community to study systems for ambient intelligence has been really strong. Usually, the systems developed so far base their analysis on images acquired by automatic cameras. In this paper, we propose a way to develop new smart systems that are able to actively decide both what to see and how to ...
MICHELONI, Christian, FORESTI, Gian Luca
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Parameter tuning for the MAX expert system
Proceedings Sixth International Conference on Tools with Artificial Intelligence. TAI 94, 2002We investigate methods for tuning numeric parameters in Nynex MAX, a telephone trouble screening expert system. Steepest descent, hillclimbing, and simulated annealing parameter adjustment strategies are applied to the problems of maximizing classification accuracy and minimizing misclassification cost.
Christopher J. Merz, Michael J. Pazzani
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