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Hybrid Algorithm (hybrid + algorithm)

Distribution by Scientific Domains
Engineering38%

Selected Abstracts

Fast BVH Construction on GPUs

COMPUTER GRAPHICS FORUM, Issue 2 2009
C. Lauterbach
We present two novel parallel algorithms for rapidly constructing bounding volume hierarchies on manycore GPUs. The first uses a linear ordering derived from spatial Morton codes to build hierarchies extremely quickly and with high parallel scalability. The second is a top-down approach that uses the surface area heuristic (SAH) to build hierarchies optimized for fast ray tracing. Both algorithms are combined into a hybrid algorithm that removes existing bottlenecks in the algorithm for GPU construction performance and scalability leading to significantly decreased build time. The resulting hierarchies are close in to optimized SAH hierarchies, but the construction process is substantially faster, leading to a significant net benefit when both construction and traversal cost are accounted for. Our preliminary results show that current GPU architectures can compete with CPU implementations of hierarchy construction running on multicore systems. In practice, we can construct hierarchies of models with up to several million triangles and use them for fast ray tracing or other applications. [source]

Hybrid Meta-Heuristic Algorithm for the Simultaneous Optimization of the O,D Trip Matrix Estimation

COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 6 2004
Antony Stathopoulos
These include a genetic algorithm (GA), a simulated annealing (SA) algorithm, and a hybrid algorithm (GASA) based on the combination of GA and SA. The computational performance of the three algorithms is evaluated and compared by implementing them on a realistic urban road network. The results of the simulation tests demonstrate that SA and GASA produce a more accurate final solution than GA, whereas GASA shows a superior convergence rate, that is, faster improvement from the initial solution, in comparison to SA and GA. In addition, GASA produces a final solution that is more robust and less dependent on the initial demand pattern, in comparison to that obtained from a greedy search algorithm. [source]

Transmission network expansion planning with security constraints based on bi-level linear programming

EUROPEAN TRANSACTIONS ON ELECTRICAL POWER, Issue 3 2009
Hong Fan
Abstract In deregulated power market, multiple conflicting objectives with many constraints should be balanced in transmission planning. The primary objective is to ensure the reliable supply to the demand as economically as possible. In this paper, a new bi-level linear programming model for transmission network expansion planning (TNEP) with security constraints has been proposed. The modeling improves traditional building style by adding reliability planning into economy planning as constraints, letting optimal planning strategy be more economic and highly reliable. A hybrid algorithm which integrates improved niching genetic algorithm and prime-dual interior point method is newly proposed to solve the TNEP based on bi-level programming. The advantages of the new methodology include (1) the highest reliability planning scheme can be acquired as economically as possible; (2) new model avoids the contradictions of conflicting objectives in TNEP, and explores new ideas for TNEP modeling; (3) the proposed hybrid algorithm is able to solve bi-level programming and fully manifests the merits of two algorithms as well. Simulation results obtained from two well-known systems and comparison analysis reveal that the proposed methodology is valid. Copyright © 2008 John Wiley & Sons, Ltd. [source]

A hybrid fast algorithm for first arrivals tomography

GEOPHYSICAL PROSPECTING, Issue 5 2009
Manuela Mendes
ABSTRACT A hybrid algorithm, combining Monte-Carlo optimization with simultaneous iterative reconstructive technique (SIRT) tomography, is used to invert first arrival traveltimes from seismic data for building a velocity model. Stochastic algorithms may localize a point around the global minimum of the misfit function but are not suitable for identifying the precise solution. On the other hand, a tomographic model reconstruction, based on a local linearization, will only be successful if an initial model already close to the best solution is available. To overcome these problems, in the method proposed here, a first model obtained using a classical Monte Carlo-based optimization is used as a good initial guess for starting the local search with the SIRT tomographic reconstruction. In the forward problem, the first-break times are calculated by solving the eikonal equation through a velocity model with a fast finite-difference method instead of the traditional slow ray-tracing technique. In addition, for the SIRT tomography the seismic energy from sources to receivers is propagated by applying a fast Fresnel volume approach which when combined with turning rays can handle models with both positive and negative velocity gradients. The performance of this two-step optimization scheme has been tested on synthetic and field data for building a geologically plausible velocity model. This is an efficient and fast search mechanism, which permits insertion of geophysical, geological and geodynamic a priori constraints into the grid model and ray path is completed avoided. Extension of the technique to 3D data and also to the solution of ,static correction' problems is easily feasible. [source]

A hybrid Bayesian back-propagation neural network approach to multivariate modelling

INTERNATIONAL JOURNAL FOR NUMERICAL AND ANALYTICAL METHODS IN GEOMECHANICS, Issue 8 2003
C. G. Chua
Abstract There is growing interest in the use of back-propagation neural networks to model non-linear multivariate problems in geotehnical engineering. To overcome the shortcomings of the conventional back-propagation neural network, such as overfitting, where the neural network learns the spurious details and noise in the training examples, a hybrid back-propagation algorithm has been developed. The method utilizes the genetic algorithms search technique and the Bayesian neural network methodology. The genetic algorithms enhance the stochastic search to locate the global minima for the neural network model. The Bayesian inference procedures essentially provide better generalization and a statistical approach to deal with data uncertainty in comparison with the conventional back-propagation. The uncertainty of data can be indicated using error bars. Two examples are presented to demonstrate the convergence and generalization capabilities of this hybrid algorithm. Copyright © 2003 John Wiley & Sons, Ltd. [source]

A volume-of-fluid method for incompressible free surface flows

INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, Issue 12 2009
I. R. Park
Abstract This paper proposes a hybrid volume-of-fluid (VOF) level-set method for simulating incompressible two-phase flows. Motion of the free surface is represented by a VOF algorithm that uses high resolution differencing schemes to algebraically preserve both the sharpness of interface and the boundedness of volume fraction. The VOF method is specifically based on a simple order high resolution scheme lower than that of a comparable method, but still leading to a nearly equivalent order of accuracy. Retaining the mass conservation property, the hybrid algorithm couples the proposed VOF method with a level-set distancing algorithm in an implicit manner when the normal and the curvature of the interface need to be accurate for consideration of surface tension. For practical purposes, it is developed to be efficiently and easily extensible to three-dimensional applications with a minor implementation complexity. The accuracy and convergence properties of the method are verified through a wide range of tests: advection of rigid interfaces of different shapes, a three-dimensional air bubble's rising in viscous liquids, a two-dimensional dam-break, and a three-dimensional dam-break over an obstacle mounted on the bottom of a tank. The standard advection tests show that the volume advection algorithm is comparable in accuracy with geometric interface reconstruction algorithms of higher accuracy than other interface capturing-based methods found in the literature. The numerical results for the remainder of tests show a good agreement with other numerical solutions or available experimental data. Copyright © 2009 John Wiley & Sons, Ltd. [source]

Microwave imaging of parallel perfectly conducting cylinders

INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, Issue 6 2000
Anyong Qing
This paper considers microwave imaging of parallel perfectly conducting cylinders using a solution of the scattering problem by the point-matching method. A cubic B-spline, real-coded genetic algorithm and an adaptive hybrid algorithm are proposed to solve the inverse problem. Previous shape functions in trigonometric series with arbitrary coefficients are nondefinite, which intensify the ill-posedness and slow the early time convergence of the algorithm. A novel shape function based on cubic B-splines is developed and the real-coded genetic algorithm is modified accordingly. Numerical simulation examples show that the early time convergence of the real-coded genetic algorithm is improved significantly. Next, the adaptive hybrid algorithm is developed to improve the late time convergence of the cubic B-spline real-coded genetic algorithm. © 2001 John Wiley & Sons, Inc. Int J Imaging Syst Technol 11, 365,371, 2000 [source]

A fast hybrid algorithm for exoplanetary transit searches

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, Issue 2 2006
A. Collier Cameron
ABSTRACT We present a fast and efficient hybrid algorithm for selecting exoplanetary candidates from wide-field transit surveys. Our method is based on the widely used SysRem and Box Least-Squares (BLS) algorithms. Patterns of systematic error that are common to all stars on the frame are mapped and eliminated using the SysRem algorithm. The remaining systematic errors caused by spatially localized flat-fielding and other errors are quantified using a boxcar-smoothing method. We show that the dimensions of the search-parameter space can be reduced greatly by carrying out an initial BLS search on a coarse grid of reduced dimensions, followed by Newton,Raphson refinement of the transit parameters in the vicinity of the most significant solutions. We illustrate the method's operation by applying it to data from one field of the SuperWASP survey, comprising 2300 observations of 7840 stars brighter than V= 13.0. We identify 11 likely transit candidates. We reject stars that exhibit significant ellipsoidal variations caused indicative of a stellar-mass companion. We use colours and proper motions from the Two Micron All Sky Survey and USNO-B1.0 surveys to estimate the stellar parameters and the companion radius. We find that two stars showing unambiguous transit signals pass all these tests, and so qualify for detailed high-resolution spectroscopic follow-up. [source]

A projected-steepest-descent potential-reduction algorithm for convex programming problems

NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS, Issue 10 2004
Yixun Shi
Abstract A recent work of Shi (Numer. Linear Algebra Appl. 2002; 9: 195,203) proposed a hybrid algorithm which combines a primal-dual potential reduction algorithm with the use of the steepest descent direction of the potential function. The complexity of the potential reduction algorithm remains valid but the overall computational cost can be reduced. In this paper, we make efforts to further reduce the computational costs. We notice that in order to obtain the steepest descent direction of the potential function, the Hessian matrix of second order partial derivatives of the objective function needs to be computed. To avoid this, we in this paper propose another hybrid algorithm which uses a projected steepest descent direction of the objective function instead of the steepest descent direction of the potential function. The complexity of the original potential reduction algorithm still remains valid but the overall computational cost is further reduced. Our numerical experiments are also reported. Copyright © 2004 John Wiley & Sons, Ltd. [source]

A New Numerical Approach for a Detailed Multicomponent Gas Separation Membrane Model and AspenPlus Simulation

CHEMICAL ENGINEERING & TECHNOLOGY (CET), Issue 7 2005
M. H. Murad Chowdhury
Abstract A new numerical solution approach for a widely accepted model developed earlier by Pan [1] for multicomponent gas separation by high-flux asymmetric membranes is presented. The advantage of the new technique is that it can easily be incorporated into commercial process simulators such as AspenPlusTM [2] as a user-model for an overall membrane process study and for the design and simulation of hybrid processes (i.e., membrane plus chemical absorption or membrane plus physical absorption). The proposed technique does not require initial estimates of the pressure, flow and concentration profiles inside the fiber as does in Pan's original approach, thus allowing faster execution of the model equations. The numerical solution was formulated as an initial value problem (IVP). Either Adams-Moulton's or Gear's backward differentiation formulas (BDF) method was used for solving the non-linear differential equations, and a modified Powell hybrid algorithm with a finite-difference approximation of the Jacobian was used to solve the non-linear algebraic equations. The model predictions were validated with experimental data reported in the literature for different types of membrane gas separation systems with or without purge streams. The robustness of the new numerical technique was also tested by simulating the stiff type of problems such as air dehydration. This demonstrates the potential of the new solution technique to handle different membrane systems conveniently. As an illustration, a multi-stage membrane plant with recycle and purge streams has been designed and simulated for CO2 capture from a 500,MW power plant flue gas as a first step to build hybrid processes and also to make an economic comparison among different existing separation technologies available for CO2 separation from flue gas. [source]