Subject hidden layers

Artificial neural networks (ANN) are computing tools made up of simple, interconnected processing elements called neurons. The neurons are arranged in layers. The feed-forward network consists of an input layer, one or more hidden layers, and an output layer. ANNs are known to be well suited for assimilating knowledge about complex processes if they are properly subjected to input-output patterns about the process. 

M1 Samples preparation Orthogonal design and normalization of geotechnical parameters within parametric domain need to be implemented. The map from parameters to deformation need to be created via forward FEM calculation. It is presented in step 1 and 2. M2 Configuration of neural network One hidden layer and four hidden neurons were set up. Three input neurons and two output neurons were set up, which is subject to the number of displacement observation nodes and parameters to be inversed. In this case, the three input neurons are the detected deformations of three groups, and the two output neurons are the unloading modulus of clay and sand layers of the slope. 

The surface of Venus is hidden under an unbroken layer of clouds 45-60 km above it. Recently, the planet has been subjected to a complete cartography by radar satellites. Its atmosphere contains 96% CO2 by volume, the remainder consisting of N2, SO2, sulphur particles, H2SO4 droplets, various reaction products and a trace of water vapour. The water is probably subject to photolytic decomposition. Noble gases are more abundant than on Earth 36Ar by a factor of 500, neon by a factor of 2,700, and D (deuterium) by a factor of 400. 

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