4,509 research outputs found

    Embrapa Trigo: carteira de projetos de pesquisa e desenvolvimento em 2010.

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    bitstream/CNPT-2010/41153/1/p-do120.pd

    Embrapa Trigo: carteira de projetos de Pesquisa e Desenvolvimento em 2008.

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    bitstream/CNPT-2010/40710/1/p-do92.pd

    Entropy diversity in multi-objective particle swarm optimization

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    Multi-objective particle swarm optimization (MOPSO) is a search algorithm based on social behavior. Most of the existing multi-objective particle swarm optimization schemes are based on Pareto optimality and aim to obtain a representative non-dominated Pareto front for a given problem. Several approaches have been proposed to study the convergence and performance of the algorithm, particularly by accessing the final results. In the present paper, a different approach is proposed, by using Shannon entropy to analyzethe MOPSO dynamics along the algorithm execution. The results indicate that Shannon entropy can be used as an indicator of diversity and convergence for MOPSO problems

    Dynamical modelling of a genetic algorithm

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    This work addresses the signal propagation and the fractional-order dynamics during the evolution of a genetic algorithm (GA). In order to investigate the phenomena involved in the GA population evolution, the mutation is exposed to excitation perturbations during some generations and the corresponding fitness variations are evaluated. Three distinct fitness functions are used to study their influence in the GA dynamics. The input and output signals are studied revealing a fractional-order dynamic evolution, characteristic of a long-term system memory

    Manipulator trajectory planning using a MOEA

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    Generating manipulator trajectories considering multiple objectives and obstacle avoidance is a non-trivial optimization problem. In this paper a multi-objective genetic algorithm based technique is proposed to address this problem. Multiple criteria are optimized considering up to five simultaneous objectives. Simulation results are presented for robots with two and three degrees of freedom, considering two and five objectives optimization. A subsequent analysis of the spread and solutions distribution along the converged non-dominated Pareto front is carried out, in terms of the achieved diversity

    On the width of the last scattering surface

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    We discuss the physical effects of some accelerated world models on the width of the last scattering surface (LSS) of the cosmic microwave background radiation (CMBR). The models considered in our analysis are X-matter (XCDM) and a Chaplygin type gas. The redshift of the LSS does not depend on the kind of dark energy (if XCDM of Chaplygin). Further, for a Chaplygin gas, the width of the LSS is also only weakly dependent on the kind of scenario (if we have dark energy plus cold dark matter or the unified picture).Comment: 10 pages, 1 figure, 2 tables, accepted to IJMP

    Robotic synthesis using a hierarchical multi-objective evolutionary algorithm

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    This paper addresses the robotic manipulator synthesis problem considering multiple design criteria simultaneously. This is a complex problem suitable for the application of multi-objective genetic algorithms. Thus, an hierarchical multi-objective genetic algorithm is proposed to generate a robot structure and corresponding manipulating trajectories. The design aim is to minimize the trajectory space ripple, the initial and final torques while optimizing the mechanical structure. Simulation results are presented concerning the solution of a structure synthesis problem with the optimization of three objectives.N/

    A Real-Time Optimization for 2R Manipulators

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    This work proposes a real-time algorithm to generate a trajectory for a 2 link planar robotic manipulator. The objective is to minimize the space/time ripple and the energy requirements or the time duration in the robot trajectories. The proposed method uses an off line genetic algorithm to calculate every possible trajectory between all cells of the workspace grid. The resultant trajectories are saved in several trees. Then any trajectory requested is constructed in real-time, from these trees. The article presents the results for several experiments
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