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International Conference on Hybrid Intelligent Systems (HIS)

作者： C.M. Fernandes J.J. Merelo A.C. Rosa LaSEEB-ISR-IST IST Technical University of Lisbon Portugal Department of Architecture and Computer Technology University of Granada Spain

This paper investigates the behavior of the adaptive dissortative mating genetic algorithm (ADMGA) on dynamic problems and compares it with other genetic algorithms (GA). ADMGA is a non-random mating algorithm that selects parents according to their Hamming distance, via a self-adjustable threshold value. The resulting method, by keeping population diversity during the run, provides new means for GAs to deal with dynamic problems, which demand high diversity in order to track the optima. Tests conducted on combinatorial and trap functions indicate that ADMGA is more robust than traditional GAs and it is capable of outperforming a previously proposed dissortative scheme on a wide range of tests.

关键词： Heuristic algorithms Gallium Optimization Hamming distance Biological cells Steady-state Frequency diversity

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A motion compensated filtering approach to remove sunlight flicker in shallow water images

A motion compensated filtering approach to remove sunlight f...

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OCEANS

作者： Nuno Gracias Shahriar Negahdaripour Laszlo Neumann Ricard Prados Rafael Garcia Underwater Vision Laboratory Computer Architecture and Technology Department University of Girona Girona Spain Underwater Vision and Imaging Laboratory Electrical and Computer Engineering Department University of Miami Coral Gables FL USA

ISBN: (纸本)9781424426195

A common problem in video surveys in very shallow waters is the presence of strong light fluctuations, due to sun light refraction. Refracted sunlight casts fast moving patterns, which can significantly degrade the quality of the acquired data. Motivated by the growing need to improve the quality of shallow water imagery, we propose a method to remove sunlight patterns in video sequences. The method exploits the fact that video sequences allow several observations of the same area of the sea floor, over time. It is based on computing the image difference between a given reference frame and the temporal median of a registered set of neighboring images. A key observation is that this difference will have two components with separable spectral content. One is related to the illumination field (lower spatial frequencies) and the other to the registration error (higher frequencies). The illumination field, recovered by lowpass filtering, is used to correct the reference image. In addition to removing the sunflickering patterns, an important advantage of the approach is the ability to preserve the sharpness in corrected image, even in the presence of registration inaccuracies. The effectiveness of the method is illustrated in image sets acquired under strong camera motion containing non-rigid benthic structures. The results testify the good performance and generality of the approach.

关键词： Filtering Optical refraction Video sequences Lighting Frequency Fluctuations Sun Degradation Sea floor Cameras

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Parameter Estimation for Radial Basis Function Neural Network Design by Means of Two Symbiotic Algorithms

Parameter Estimation for Radial Basis Function Neural Networ...

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International Conference on Advanced Engineering Computing and Applications in Sciences (ADVCOMP)

作者： Elisabet Parras-Gutierrez M. Jose del Jesus Victor M. Rivas Juan J. Merelo Department of Computer Sciences Jaen Spain Universidad de Jaen Jaen JaÃ©n ES Department of Computers Architecture and Technology Granada Spain

Increasing the usability of traditional methods is one of the key issues on future trends in data mining. Nevertheless, most data mining algorithms need to be given a suitable set of parameters for every problem they face, thus methods to automatically search the values of these parameters are required. This paper introduces two co-evolutionary algorithms intended to automatically establish the parameters needed to design radial basis function neural networks. Results show that both algorithms can be effectively used to obtain good models, while reducing significantly the number of parameters to be fixed at hand.

关键词： Symbiosis Classification algorithms Algorithm design and analysis Evolutionary computation Evolution (biology) Neurons Artificial neural networks

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Error Restricted Piecewise Linear Representation of Time Series Based on Special Points

Error Restricted Piecewise Linear Representation of Time Ser...

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World Congress on Intelligent Control and Automation (WCICA)

作者： Pengtao Jia Huacan He Tao Sun School of Computer Science Northwestern Polytechnical University Xi'an China Department of Computer Science Xi''an University of Science and Technology Xi'an China School of Architecture and Civil Engineering Xi''an University of Science and Technology Xi'an China

Time series composed of a series of data observed according to time sequence. There are large numbers of time series in the field of automatic control. Usually time series data is massive. Sometimes, it is inefficient or impractical to mine the original time series data directly. So time series should be represented on higher level. Piecewise Linear Representation is perhaps the most frequently used representation with lower dimensions of index structure and the faster speed of calculation. But PLR needs a parameter k given by users and to make certain k is not easy for the users. We put forward an algorithm of error restricted piecewise linear representation based on special points that can give the number of fitting lines automatically according to a given error e. And it has lower time complexity than other error restricted algorithm, such as sliding windows, Bottom-Up, Top-Down. According to experiments our algorithm leads to less fitting error and better performance than other algorithms. So it would be more efficient in the real application of control fields.

关键词： Time series analysis Approximation algorithms Fitting Approximation methods Complexity theory Piecewise linear approximation Algorithm design and analysis

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Maximum Coverage at Minimum Cost for Multi-Domain IP/MPLS Networks

Maximum Coverage at Minimum Cost for Multi-Domain IP/MPLS Ne...

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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： M. Yannuzzi X. Masip-Bruin R. Serral-Gracia E. Marin-Tordera A. Sprintson A. Orda Department of Computer Architecture Technical University of Catalonia Catalonia Spain Department of Electrical and Computer Engineering Texas A and M University College Station TX USA Department of Electrical Engineering Technion-Israel Institute of Technology Haifa Israel

At present, service providers have several incentives to extend the reach of long-lived MPLS paths across domains. Providers, however, will face a number of trade-offs while choosing the optimal set of MPLS paths to be established. In this paper, we focus on the multi-objective decision problem of maximizing the traffic demands to be covered by long-lived MPLS paths from a source domain S to its major destination domains, while minimizing the monetary costs incurred. The problem is formulated subject to a budget constraint, which assures the minimum expected revenue for the provider in S. A major advantage of the analysis and solution proposed in this paper is that it can be easily generalized, and applied in other settings where constrained problems considering maximum coverage vs. cost are critical.

关键词： Costs Multiprotocol label switching Virtual private networks Routing Telecommunication traffic computer networks Communications Society computer architecture USA Councils Marine technology

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Application of neural network and expert system in gearbox test

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Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and technology (Natural Science Edition) 2008年第SUPPL. 1期36卷 53-56页

作者： Zhang, Guangbin Ge, Yunjian Fang, Kai Institute of Intelligent Machines Chinese Academy of Sciences Hefei 230031 China Department of Automation University of Science and Technology of China Hefei 230026 China Department of Computer Engineering Anhui University of Architecture Hefei 230022 China

According to complex of gearbox test online, this paper introduces a gearbox test system based on automatic shift manipulator. Optimal shift law plays an important role in improving work efficiency and prolonging service life of gearbox. It was more intelligent that judging optimal shift by using neural network. The shift procedure was a complicated nonlinear time-varying one, involving many variables, so the expert system was used to control shift procedure. Then it was a more personification procedure owing to fast and accurate operations. Good running state of system proved success for application of neural network and expert system in product test. Moreover the system had some guiding significance in intelligent and personification control of manipulator.

关键词： Expert systems

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Still image copy detection algorithm robust to basic image modifications

Still image copy detection algorithm robust to basic image m...

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International Symposium on Electronics in Marine (ELMAR)

作者： Karol Wnukowicz Grzegorz Galinski Ruben Tous Institute of Radioelectronics Warsaw University of Technology Warsaw Poland Computer Architecture Department Universitat Poliltècnica de Catalunya Barcelona Spain

ISBN: (纸本)9781424433643

The paper presents a method for content based still-image replica detection. This method uses a compact image signature which depends on image content and is invariant to many widely used image processing techniques, such as lossy compression, resizing, resampling, color enhancements and simple rotations. The signature is designed to be usable in big image database: it has small size (a few dozen bytes), the extraction is fast and the comparison of image signatures is very fast. More than million of image signatures per second can be compared on a modern PC. Usage of the method within a framework for digital rights infringements detection in the World Wide Web is also discussed.

关键词： Detection algorithms Robustness Image processing Image coding computer architecture Electronic mail Color Image databases Web sites Image retrieval

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Better learning of neural networks using functional graph for analysis of wireless network

Better learning of neural networks using functional graph fo...

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International Conference on computer and Communication Engineering, ICCCE

作者： V. Joseph Raj Heren Chellam G. Stella Morris Department of Computer Engineering Faculty of Architecture and Engineering European University of Lefke North Cyprus Mersin 10 TURKEY Department of Computer Science Government Arts College for Women Alagappa University INDIA 3Department of Electrical and Computer Engineering Manukau Institute of Technology (M.I.T) Auckland NEW ZEALAND

Neural networks have been used as an effective method for solving many problems in a wide range of application areas. As neural networks are being more and more widely used in recent years, the need for their more formal definition becomes increasingly apparent. This paper presents a novel architecture of neural network models using the functional graph. The network creates a graph representation by dynamically allocating nodes to code local form attributes and establishing arcs to link them. In this paper application of functional graph in the architecture of electronic neural network, opto-electronic neural network and genetic neural network are detailed with experimental results. Learning is defined in terms of functional graph. The proposed architectures are applied in evaluating 3G wireless network performance.

关键词： Neural networks Wireless networks Artificial neural networks Biological neural networks Neurons Genetic algorithms computer networks computer architecture computer science Government

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Research of information retrieval method based on fuzzy rough sets theory

Research of information retrieval method based on fuzzy roug...

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IEEE International Conference on Granular Computing (GRC)

作者： Dekun Tan Hui Sun Minjun Deng Department of Computer Science and Technology Nanchang Institute of Technology Nanchang Jiangxi China School of Civil Engineering and Architecture East China Jiao Tong University Nanchang Jiangxi China

ISBN: (纸本)9781424425129

This paper proposes a new information retrieval method based on fuzzy rough sets theory. In the approach, firstly, the traditional Mutual Information function are used to compute the semantic association weight among document characteristic words, i.e., construct the thesaurus, the similar concept class of each characteristic word is mined based on it. Secondly, the fuzzy-rough set of document and query is built with thesaurus and similar concept class, its lower and upper approximation expand the expression of document and query, it implements conceptual expansion by association semantics. Finally, the semantic closeness between document and query is computed by the semantic distance on fuzzy-rough set, the ordinal results are returned to user according to the close degree value. The user can also adjust support threshold to get his satisfactory research objects through feedback information. This method can realize conceptual retrieval. At the end of the paper, an example is given for further illustration.

关键词： Approximation methods Set theory Information retrieval Thesauri Mutual information Data mining Computational modeling

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Comparing multiobjective evolutionary ensembles for minimizing type I and II errors for bankruptcy prediction

Comparing multiobjective evolutionary ensembles for minimizi...

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Congress on Evolutionary Computation

作者： E. Alfaro-Cid P. A. Castillo A. Esparcia K. Sharman J.J. Merelo A. Prieto A.M. Mora J.L.J. Laredo Instituto Tecnológico de Informática Universidad Politécnica de Valencia Spain Architecture and Computer Technology Department University of Granada Spain

In many real world applications type I (false positive) and type II (false negative) errors have to be dealt with separately, which is a complex problem since an attempt to minimize one of them usually makes the other grow. In fact, a type of error can be more important than the other, and a trade-off that minimizes the most important error type must be reached. In the case of the bankruptcy prediction problem the error type II is of greater importance, being unable to identify that a company is at risk causes problems to creditors and slows down the taking of measures that may solve the problem. Despite the importance of type II errors, most bankruptcy prediction methods take into account only the global classification error. In this paper we propose and compare two methods to optimize both error types in classification: artificial neural networks and function trees ensembles created through multiobjective optimization. Since the multiobjective optimization process produces a set of equally optimal results (Pareto front) the classification of the test patterns in both cases is based on the non-dominated solutions acting as an ensemble. The experiments prove that, although the best classification rates are obtained using the artificial neural network, the multiobjective genetic programming model is able to generate comparable results in the form of an analytical function.

关键词： Artificial neural networks Companies Training Evolutionary computation Optimization Genetic programming Classification algorithms

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