Ultimate Compressive Strength Prediction for Stiffened Panels by Counterpropagation Neural Networks (CPN)

Stiffened Panels are important strength members in ship and offshore structures,A new methodbased on counterpropagation neural networks(CPN)is proposed in this paper to predict the ultimate compres-sive strength of stiffened panels.Compared with two-parametric polynomial,this method can take more pa-rameters into account and make more use of experimental data.Numerical study is carried out to verify thevalidation of this method.The new method may find wide application in practical design.     

Dynamic Plastic Response of Circular Plates Resting on Fluid with Finite Deformation

This paper concerns the dynamic plastic response of a circular plate resting on fluid subjectedto a uniformly distributed rectangular load pulse with finite deformation.It is assumed that the fluid isincompressible and inviscous,and the plate is made of rigid-plastic material and simply supported along itsedge.By using the method of the Hankel integral transformation,the nonuniform fluid resistance is de-rived as the plate and the fluid is coupled.Finally,an analytic solution for a circular plate under a mediumload is obtained according to the equations of motion of the plate with finite deformation.     

Remote sensing image classification with GIS data based on spatial data mining techniques

Data mining techniques are used to discover knowledge from GIS database in order to improve remote sensing image classification.Two learning granularities are proposed for inductive learning from spatial data,one is spatial object granularity,the other is pixel granularity.We also present an approach to combine inductive learning with conventional image classification methods,which selects class probability of Bayes classification as learning attributes.A land use classification experiment is performed in the Beijing area using SPOT multi-spectral image and GIS data.Rules about spatial distribution patterns and shape features are discovered by C5.0 inductive learning algorithm and then the image is reclassified by deductive reasoning.Comparing with the result produced only by Bayes classification,the overall accuracy increased by 11% and the accuracy of some classes,such as garden and forest,increased by about 30%.The results indicate that inductive learning can resolve spectral confusion to a great extent.Combining Bayes method with inductive learning not only improves classification accuracy greatly,but also extends the classification by subdividing some classes with the discovered knowledge.     

4D data fusion technique in urban waterlog-draining decision support system

This paper studies urban waterlog-draining decision support system based on the 4D data fusion technique.4D data includes DEM,DOQ,DLG and DRG.It supplies entire databases for waterlog forecast and analysis together with non-spatial fundamental database.Data composition and reasoning are two key steps of 4D data fusion.Finally,this paper gives a real case: Ezhou Waterlog-Draining Decision Support System (EWDSS) with two application models,i.e.,DEM application model,water generating and draining model.     

Quality of man in India: Some perceptions

The paper is an attempt to focus on some of the issues of quality of man in India. It is hypothesised that the culture is changing towards undefined goals based on materialistic grounds of recent systems. The issues putforth here need a careful consideration on philosophical levels to reduce tensions in the society and man.