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EN
To obtain the mechanical energy of waves from arbitrary directions, the vibration absorbers of wave energy converters (WEC) are usually vertically axisymmetric. In such case, the wave-body interaction hydrodynamics is an essential research topic to obtain high-efficiency wave energy. In this paper, a semi-analytical method of decomposing the complex axisymmetric boundary into several ring-shaped stepped surfaces based upon the boundary approximation method (BAM) is introduced and examined. The hydrodynamic loads and parameters, such as the wave excitation forces, added mass and radiation damping of the vertical axisymmetric oscillating buoys, can then be achieved by using the new boundary discretisation method. The calculations of the wave forces and hydrodynamic coefficients show good convergence with the number of discretisation increases. Comparison between the constringent results and the results of the conventional method also verifies the feasibility of the method. Then, simulations and comparisons of the hydrodynamic forces, motions and wave power conversions of the buoys with series draught and displacement ratios in regular and irregular waves are conducted. The calculation results show that the geometrical shape has a great effect on the hydrodynamic and wave power conversion performance of the absorber. In regular waves, though the concave buoy has the lowest wave conversion efficiency, it has the largest frequency bandwidth for a given draught ratio, while in irregular waves, for a given draught ratio, the truncated cylindrical buoy has the best wave power conversion, and for a given displacement of the buoy, the concave buoy shows the best wave power conversion ability.
2
Content available Recognizing Sharp Features of 2-D Shapes
EN
We present an efficient algorithm for recognizing and extracting sharp-features from complex polygonal shapes. The algorithm executes in O(n²) time, where n is the number of vertices in the polygon. Sharp-feature extraction algorithms can be useful as a pre-processing step for measuring shape-similarity between polygonal shapes.
3
Content available remote Relation between VGA-classifier and MLP : determination of network architecture
EN
An analogy between a genetic algorithm based pattern classification scheme (where hyper-planes are used to approximate the class boundaries through searching) and multiplayer per-ceptron (MLP) based classifier is established. Based on this, a method for determining the MLP architecture automatically is described. It is shown that the architecture would need at-most two hidden layers, the neurons of which are responsible for generating hyperplanes and regions. The neurons in the second hidden and output layers perform the AND & OR func-tions respectively. The methodology also includes a post processing step which automatically removes any redundant neuron in the hidden/output layer. An extensive comparative study of the performance of the MLP, thus derived using the proposed method, with those of several other conventional MLP's is presented for different data sets.
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