12 resultados para Dynamic search fireworks algorithm with covariance mutation
em Universidade do Minho
Resumo:
Firefly Algorithm is a recent swarm intelligence method, inspired by the social behavior of fireflies, based on their flashing and attraction characteristics [1, 2]. In this paper, we analyze the implementation of a dynamic penalty approach combined with the Firefly algorithm for solving constrained global optimization problems. In order to assess the applicability and performance of the proposed method, some benchmark problems from engineering design optimization are considered.
Resumo:
A search for new particles that decay into top quark pairs is reported. The search is performed with the ATLAS experiment at the LHC using an integrated luminosity of 20.3 fb−1 of proton-proton collision data collected at a centre-of-mass energy of s√=8 TeV. The lepton-plus-jets final state is used, where the top pair decays to W+bW−b¯¯, with one W boson decaying leptonically and the other hadronically. The invariant mass spectrum of top quark pairs is examined for local excesses or deficits that are inconsistent with the Standard Model predictions. No evidence for a top quark pair resonance is found, and 95% confidence-level limits on the production rate are determined for massive states in benchmark models. The upper limits on the cross-section times branching ratio of a narrow Z′ boson decaying to top pairs range from 4.2 pb to 0.03 pb for resonance masses from 0.4 TeV to 3.0 TeV. A narrow leptophobic topcolour Z′ boson with mass below 1.8 TeV is excluded. Upper limits are set on the cross-section times branching ratio for a broad colour-octet resonance with Γ/m = 15% decaying to tt¯. These range from 4.8 pb to 0.03 pb for masses from 0.4 TeV to 3.0 TeV. A Kaluza-Klein excitation of the gluon in a Randall-Sundrum model is excluded for masses below 2.2 TeV.
Resumo:
The jet energy scale (JES) and its systematic uncertainty are determined for jets measured with the ATLAS detector using proton–proton collision data with a centre-of-mass energy of s√=7 TeV corresponding to an integrated luminosity of 4.7 fb −1 . Jets are reconstructed from energy deposits forming topological clusters of calorimeter cells using the anti- kt algorithm with distance parameters R=0.4 or R=0.6 , and are calibrated using MC simulations. A residual JES correction is applied to account for differences between data and MC simulations. This correction and its systematic uncertainty are estimated using a combination of in situ techniques exploiting the transverse momentum balance between a jet and a reference object such as a photon or a Z boson, for 20≤pjetT<1000 GeV and pseudorapidities |η|<4.5 . The effect of multiple proton–proton interactions is corrected for, and an uncertainty is evaluated using in situ techniques. The smallest JES uncertainty of less than 1 % is found in the central calorimeter region ( |η|<1.2 ) for jets with 55≤pjetT<500 GeV . For central jets at lower pT , the uncertainty is about 3 %. A consistent JES estimate is found using measurements of the calorimeter response of single hadrons in proton–proton collisions and test-beam data, which also provide the estimate for pjetT>1 TeV. The calibration of forward jets is derived from dijet pT balance measurements. The resulting uncertainty reaches its largest value of 6 % for low- pT jets at |η|=4.5 . Additional JES uncertainties due to specific event topologies, such as close-by jets or selections of event samples with an enhanced content of jets originating from light quarks or gluons, are also discussed. The magnitude of these uncertainties depends on the event sample used in a given physics analysis, but typically amounts to 0.5–3 %.
Resumo:
Measurements of inclusive jet production are performed in pp and Pb+Pb collisions at sNN−−−√=2.76 TeV with the ATLAS detector at the LHC, corresponding to integrated luminosities of 4.0 pb−1 and 0.14 nb−1 , respectively. The jets are identified with the anti-kt algorithm with R=0.4, and the spectra are measured over the kinematic range of jet transverse momentum 32
Resumo:
The inclusive jet cross-section is measured in proton--proton collisions at a centre-of-mass energy of 7 TeV using a data set corresponding to an integrated luminosity of 4.5 fb−1 collected with the ATLAS detector at the Large Hadron Collider in 2011. Jets are identified using the anti-kt algorithm with radius parameter values of 0.4 and 0.6. The double-differential cross-sections are presented as a function of the jet transverse momentum and the jet rapidity, covering jet transverse momenta from 100 GeV to 2 TeV. Next-to-leading-order QCD calculations corrected for non-perturbative effects and electroweak effects, as well as Monte Carlo simulations with next-to-leading-order matrix elements interfaced to parton showering, are compared to the measured cross-sections. A quantitative comparison of the measured cross-sections to the QCD calculations using several sets of parton distribution functions is performed.
Resumo:
This Letter presents measurements of correlated production of nearby jets in Pb+Pb collisions at sNN−−−√=2.76 TeV using the ATLAS detector at the Large Hadron Collider. The measurement was performed using 0.14 nb−1 of data recorded in 2011. The production of correlated jet pairs was quantified using the rate, RΔR, of ``neighbouring'' jets that accompany ``test'' jets within a given range of angular distance, ΔR, in the pseudorapidity--azimuthal angle plane. The jets were measured in the ATLAS calorimeter and were reconstructed using the anti-kt algorithm with radius parameters d=0.2, 0.3, and 0.4. RΔR was measured in different Pb+Pb collision centrality bins, characterized by the total transverse energy measured in the forward calorimeters. A centrality dependence of RΔR is observed for all three jet radii with RΔR found to be lower in central collisions than in peripheral collisions. The ratios formed by the RΔR values in different centrality bins and the values in the 40--80 % centrality bin are presented.
Resumo:
The Smart Drug Search is publicly accessible at http://sing.ei.uvigo.es/sds/. The BIOMedical Search Engine Framework is freely available for non-commercial use at https://github.com/agjacome/biomsef
Resumo:
Double-differential three-jet production cross-sections are measured in proton--proton collisions at a centre-of-mass energy of s√=7TeV using the ATLAS detector at the Large Hadron Collider. The measurements are presented as a function of the three-jet mass (mjjj), in bins of the sum of the absolute rapidity separations between the three leading jets (|Y∗|). Invariant masses extending up to 5 TeV are reached for 8<|Y∗|<10. These measurements use a sample of data recorded using the ATLAS detector in 2011, which corresponds to an integrated luminosity of 4.51fb−1. Jets are identified using the anti-kt algorithm with two different jet radius parameters, R=0.4 and R=0.6. The dominant uncertainty in these measurements comes from the jet energy scale. Next-to-leading-order QCD calculations corrected to account for non-perturbative effects are compared to the measurements. Good agreement is found between the data and the theoretical predictions based on most of the available sets of parton distribution functions, over the full kinematic range, covering almost seven orders of magnitude in the measured cross-section values.
Resumo:
Dissertação de mestrado em Engenharia de Sistemas
Resumo:
Dissertação de mestrado em Comunicação, Arte e Cultura
Resumo:
Dissertação de mestrado em Ciências da Comunicação (área de especialização em Audiovisual e Multimédia)
Resumo:
The artificial fish swarm algorithm has recently been emerged in continuous global optimization. It uses points of a population in space to identify the position of fish in the school. Many real-world optimization problems are described by 0-1 multidimensional knapsack problems that are NP-hard. In the last decades several exact as well as heuristic methods have been proposed for solving these problems. In this paper, a new simpli ed binary version of the artificial fish swarm algorithm is presented, where a point/ fish is represented by a binary string of 0/1 bits. Trial points are created by using crossover and mutation in the different fi sh behavior that are randomly selected by using two user de ned probability values. In order to make the points feasible the presented algorithm uses a random heuristic drop item procedure followed by an add item procedure aiming to increase the profit throughout the adding of more items in the knapsack. A cyclic reinitialization of 50% of the population, and a simple local search that allows the progress of a small percentage of points towards optimality and after that refines the best point in the population greatly improve the quality of the solutions. The presented method is tested on a set of benchmark instances and a comparison with other methods available in literature is shown. The comparison shows that the proposed method can be an alternative method for solving these problems.