Based on seismic damage data of gas pipeline network, obtained through scientific investigation in 18 cities/counties, seismic damage appearances of gas pipeline which are made of different materials are summarized and compared, and their impacts on gas supply function are studied. Then the use status of pipeline of different materials and the reasons of causing damages are analyzed. And some earthquake resistant countermeasures are proposed to reduce the seismic damages.
Wavelet neural network(WNN) was applied to predicate the cortisol solubility. The model consists of a multilayer feedforward hierarchical structure, and the flow of information is directed from the input to the output layer by using wavelet transforms to achieve faster convergence. By adaptively adjusting the number of training data involved during training, an adaptive robust learning algorithm is derived for improvement of the efficiency of the network. The neural network was trained and simulated cortisol solubility with different input and output parameters. Simulation results confirmed that this approach gave more accurate predictions solubility.
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