987 resultados para PARTICLE
Resumo:
The most common approach to decision making in multi-objective optimisation with metaheuristics is a posteriori preference articulation. Increased model complexity and a gradual increase of optimisation problems with three or more objectives have revived an interest in progressively interactive decision making, where a human decision maker interacts with the algorithm at regular intervals. This paper presents an interactive approach to multi-objective particle swarm optimisation (MOPSO) using a novel technique to preference articulation based on decision space interaction and visual preference articulation. The approach is tested on a 2D aerofoil design case study and comparisons are drawn to non-interactive MOPSO. © 2013 IEEE.
Resumo:
We consider the smoothing problem for a class of conditionally linear Gaussian state-space (CLGSS) models, referred to as mixed linear/nonlinear models. In contrast to the better studied hierarchical CLGSS models, these allow for an intricate cross dependence between the linear and the nonlinear parts of the state vector. We derive a Rao-Blackwellized particle smoother (RBPS) for this model class by exploiting its tractable substructure. The smoother is of the forward filtering/backward simulation type. A key feature of the proposed method is that, unlike existing RBPS for this model class, the linear part of the state vector is marginalized out in both the forward direction and in the backward direction. © 2013 IEEE.
Resumo:
An integrated 2-D model of a lithium ion battery is developed to study the mechanical stress in storage particles as a function of material properties. A previously developed coupled stress-diffusion model for storage particles is implemented in 2-D and integrated into a complete battery system. The effect of morphology on the stress and lithium concentration is studied for the case of extraction of lithium in terms of previously developed non-dimensional parameters. These non-dimensional parameters include the material properties of the storage particles in the system, among other variables. We examine particles functioning in isolation as well as in closely-packed systems. Our results show that the particle distance from the separator, in combination with the material properties of the particle, is critical in predicting the stress generated within the particle. © 2012 Springer-Verlag.
Resumo:
A High Temperature Condensation Particle Counter (HT-CPC) is described that operates at an elevated temperature of up to ca. 300. °C such that volatile particles from typical combustion sources are not counted. The HT-CPC is functionally identical to a conventional CPC, the main challenge being to find suitable non-hazardous working fluids, with good stability, and an appropriate vapour pressure. Some key design features are described, and results of modelling which predict the HT-CPC counting efficiency. Experimental results are presented for several candidate fluids when the HT-CPC was challenged with ambient, NaCl and diesel soot particles, and the results show good agreement with modelled predictions, and confirm that counting of particles of diameters down to at least 10. nm was achievable. Possible applications are presented, including measurement of particles from a diesel car engine and comparison with a near PMP system. © 2014 Elsevier Ltd.
Resumo:
State-space models are successfully used in many areas of science, engineering and economics to model time series and dynamical systems. We present a fully Bayesian approach to inference and learning (i.e. state estimation and system identification) in nonlinear nonparametric state-space models. We place a Gaussian process prior over the state transition dynamics, resulting in a flexible model able to capture complex dynamical phenomena. To enable efficient inference, we marginalize over the transition dynamics function and, instead, infer directly the joint smoothing distribution using specially tailored Particle Markov Chain Monte Carlo samplers. Once a sample from the smoothing distribution is computed, the state transition predictive distribution can be formulated analytically. Our approach preserves the full nonparametric expressivity of the model and can make use of sparse Gaussian processes to greatly reduce computational complexity.
Resumo:
Sediments and soils collected from the Ya-Er Lake area in China were analysed for the polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs), polychlorinated biphenyl (PCBs), hexachlorocyclohexane (HCHs) and hexachlorobenzene (HCB). The results indicated the main pollution problems in the Ya-Er Lake area, which was heavily polluted by HCHs and chlorobenzenes, now is dominantly polluted by PCDD/Fs, PCBs and HCB. The occurrence of PCDD/Fs and PCBs with relatively high levels of HpCDDs, OCDD and low chlorinated-substituted PCBs, is attributed to the discharge of waste water and biodegradation. The vertical distributions of HCH-residues are related with the content of organic carbon and particle size. Copyright (C) 1996 Elsevier Science Ltd
Resumo:
The full spectra of magnetoplasmons and single-particle excitations are obtained of coupled one-dimensional electron gases in parallel semiconductor quantum wires with tunneling. We show the effects of the interwire Coulomb interaction and the tunneling, as well as the magnetic-field-induced localization on the elementary excitations in symmetric and asymmetric coulped quantum wire structures. The interacton and resonance between the plasmon and the intersubband single-particle excitations are found in magnetic fields.
Resumo:
Particle Swarm Optimization (PSO) algorithm is often used for finding optimal solution, but it easily entraps into the local extremum in later evolution period. Based on improved chaos searching strategy, an enhanced particle swarm optimization algorithm is proposed in this study. When particles get into the local extremum, they are activated by chaos search strategy, where the chaos search area is controlled in the neighborhood of current optimal solution by reducing search area of variables. The new algorithm not only gets rid of the local extremum effectively but also enhances the precision of convergence significantly. Experiment results show that the proposed algorithm is better than standard PSO algorithm in both precision and stability.
Resumo:
We have applied the Green function theory in GW approximation to calculate the quasiparticle energies for semiconductors Si and GaAs. Good agreements of the calculated excitation energies and fundamental energy gaps with the experimental band structures were achieved. We obtained the calculated fundamental gaps of Si and GaAs to be 1.22 and 1.42 eV in comparison to the experimental values of 1.17 and 1.52 eV, respectively. Ab initio pseudopotential method has been used to generate basis wavefunctions and charge densities for calculating dielectric matrix elements and electron self-energies.
Resumo:
We have applied the Green-function method in the GW approximation to calculate quasiparticle energies for the semiconductors GaP and GaAs. Good agreement between the calculated excitation energies and the experimental results was achieved. We obtained calculated direct band gaps of GaP and GaAs of 2.93 and 1.42 eV, respectively, in comparison with the experimental values of 2.90 and 1.52 eV, respectively. An ab initio pseudopotential method has been used to generate basis wave functions and charge densities for calculating the dielectric matrix elements and self-enegies. To evaluate the dynamical effects of the screened interaction, the generalized-plasma-pole model has been utilized to extend the dielectric matrix elements from static results to finite frequencies. We presen the calculated quasiparticle energies at various high-symmetry points of the Brillouin zone and compare them with the experimental results and other calculations.