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121.
Luis Rodero-Merino Antonio Fernández Anta Luis López Vicent Cholvi 《Computer Networks》2009,53(10):1722-1736
The problem of efficient resource location is an important open issue in P2P systems. This paper introduces DANTE, a self-adapting P2P system that changes its peer links to form topologies where resources are located in an efficient manner via random walks. Additionally, this same self-adaptation capacity makes DANTE capable of reacting to events like changes in the system load or attacks on well-connected nodes by adjusting the topology to the new scenario. This adaptive behavior emerges as the global result of the individual work of nodes, without the intervention of any central entity or the need for global knowledge. Simulations show that this adaptation process makes the system scalable, resilient to attacks, and tolerant to a high transitivity of peers. Simulations are also used to compare this solution with other well-known self-adapting P2P system. From these results it can be concluded that the topologies achieved by DANTE offer better performance. 相似文献
122.
Adaptation and application of multi-objective evolutionary algorithms for rule reduction and parameter tuning of fuzzy rule-based systems 总被引:7,自引:7,他引:0
María José Gacto Rafael Alcalá Francisco Herrera 《Soft Computing - A Fusion of Foundations, Methodologies and Applications》2009,13(5):419-436
Recently, multi-objective evolutionary algorithms have been applied to improve the difficult tradeoff between interpretability
and accuracy of fuzzy rule-based systems. It is known that both requirements are usually contradictory, however, these kinds
of algorithms can obtain a set of solutions with different trade-offs. This contribution analyzes different application alternatives
in order to attain the desired accuracy/interpr-etability balance by maintaining the improved accuracy that a tuning of membership
functions could give but trying to obtain more compact models. In this way, we propose the use of multi-objective evolutionary
algorithms as a tool to get almost one improved solution with respect to a classic single objective approach (a solution that
could dominate the one obtained by such algorithm in terms of the system error and number of rules). To do that, this work
presents and analyzes the application of six different multi-objective evolutionary algorithms to obtain simpler and still
accurate linguistic fuzzy models by performing rule selection and a tuning of the membership functions. The results on two
different scenarios show that the use of expert knowledge in the algorithm design process significantly improves the search
ability of these algorithms and that they are able to improve both objectives together, obtaining more accurate and at the
same time simpler models with respect to the single objective based approach.
相似文献
María José Gacto (Corresponding author)Email: |
Rafael AlcaláEmail: |
Francisco HerreraEmail: |
123.
Luis Gracia Carlos Perez-Vidal 《International Journal of Control, Automation and Systems》2009,7(5):764-776
This research presents a new control scheme for visual servoing that takes into account the delay introduced by image acquisition
and image processing. Firstly, previous control schemes for visual servoing are discussed and then a new control scheme is
proposed and fully described. Afterwards, the capabilities (steady-state errors, stability margins, step time response, etc.)
of the proposed control scheme and of previous ones are analytically analyzed and compared. Next, several simulations and
experimental results are provided to validate the analytical results and to illustrate the benefits of the proposed control
scheme. In particular, it is shown that this new control scheme clearly improves the performance of the previous ones. 相似文献
124.
125.
Roldão Luis de Charette Raoul Verroust-Blondet Anne 《International Journal of Computer Vision》2022,130(8):1978-2005
International Journal of Computer Vision - Semantic scene completion (SSC) aims to jointly estimate the complete geometry and semantics of a scene, assuming partial sparse input. In the last years... 相似文献
126.
A new methodology for the calibration of bond microparameters in rocks represented by a package of joined random spherical particles in the discrete element method (DEM) framework is presented. Typically, calibration is achieved through a trial-and-error procedure using several DEM simulations of uniaxial compressive tests (UCTs). The bond calibration model (BCM) does not need a time-dependent UCT-DEM simulation to establish the relation between the microproperties of the bond and the macroproperties of the rock specimen. The BCM uses matrices to describe the interaction forces exerted by bonds and, by means of an assembly process similar to the finite element method, it can describe the complex network of bonds, enabling the model to capture small variations in particle size and bond distribution as demonstrated in this work. In this work, the BCM is presented and compared with UCT simulations performed using Esys Particle software. Multiple simulations are done with constant bond properties and different particle size ratios (\(D_{MAX}/D_{MIN})\) that cause small variations in the specimen’s Young’s modulus; these variations are well captured by the BCM with an error of <10%. 相似文献
127.
Diana M. Bobrowska Justyna Czyrko Krzysztof Brzezinski Luis Echegoyen 《Fullerenes, Nanotubes and Carbon Nanostructures》2017,25(3):185-192
Carbon nano-onion/surfactant (CNO/surfactant) composites offer the possibility to easily produce the soluble nanostructures. That approach combines the hydrophilicity of surfactants with the robustness of carbon structures to produce composites with superior and unusual physicochemical properties. We used the following surfactants: hexadecyltrimethylammonium bromide (CTAB), sodium dodecyl sulfate (SDS), sodium dodecyl benzene sulfonate (SDBS), 4-(1,1,3,3-tetramethylbutyl)phenyl-polyethylene glycol (Triton X-100), and polyethylene glycol sorbitan monolaurate (Tween 20) to non-covalently modify CNO surfaces. The existence of stable CNO composites are clearly evidenced by direct transmission electron microscopy observations, which are also supported by thermogravimetric analyses. Dynamic light scattering and zeta potential confirmed their dispersion and stability. Additionally, the biological activity of well-dispersed CNO/surfactant composites against a strain of Escherichia coli was assayed. In vitro antimicrobial assays for the composites revealed that only the CNO/CTAB composite decreased cell viability. This activity could be assigned to the simple composite dissociation in water solutions, however antimicrobial properties of the composite are slightly better when compared with pure CTAB. This indicate some synergic effect with respect to the properties of the pure surfactant. 相似文献
128.
129.
Luis TruebaJr Monica A. Torres Lucie B. Johannes Daniel Rybicki 《International Journal of Material Forming》2018,11(4):559-570
Self-reacting friction stir welding (SR-FSW), also called bobbin-tool friction stir welding (BT-FSW), is a solid state welding process similar to friction stir welding (FSW) except that the tool has two opposing shoulders instead of the shoulder and a backing plate found in FSW. The tool configuration results in greater heat input and a symmetrical weld macrostructure. A significant amount of information has been published in the literature concerning traditional FSW while little has been published about SR-FSW. An optimization experiment was performed using a factorial design to evaluate the effect of process parameters on the weld temperature, surface and internal quality, and mechanical properties of self-reacting friction stir welded aluminum alloy 6061-T6 butt joints. The parameters evaluated were tool rotational speed, traverse speed, and tool plunge force. A correlation between weld temperature, defect formation (specifically galling and void formation), and mechanical properties was found. Optimum parameters were determined for the welding of 8-mm-thick 6061-T6 plate. 相似文献
130.
Juli��n Luengo Alberto Fern��ndez Salvador Garc��a Francisco Herrera 《Soft Computing - A Fusion of Foundations, Methodologies and Applications》2011,15(10):1909-1936
In the classification framework there are problems in which the number of examples per class is not equitably distributed,
formerly known as imbalanced data sets. This situation is a handicap when trying to identify the minority classes, as the
learning algorithms are not usually adapted to such characteristics. An usual approach to deal with the problem of imbalanced
data sets is the use of a preprocessing step. In this paper we analyze the usefulness of the data complexity measures in order
to evaluate the behavior of undersampling and oversampling methods. Two classical learning methods, C4.5 and PART, are considered
over a wide range of imbalanced data sets built from real data. Specifically, oversampling techniques and an evolutionary
undersampling one have been selected for the study. We extract behavior patterns from the results in the data complexity space
defined by the measures, coding them as intervals. Then, we derive rules from the intervals that describe both good or bad
behaviors of C4.5 and PART for the different preprocessing approaches, thus obtaining a complete characterization of the data
sets and the differences between the oversampling and undersampling results. 相似文献