505 results about "Artificial neural network model" patented technology

A method is described for improving the prediction accuracy and generalization performance of artificial neural network models in presence of input-output example data containing instrumental noise and / or measurement errors, the presence of noise and / or errors in the input-output example data used for training the network models create difficulties in learning accurately the nonlinear relationships existing between the inputs and the outputs, to effectively learn the noisy relationships, the methodology envisages creation of a large-sized noise-superimposed sample input-output dataset using computer simulations, here, a specific amount of Gaussian noise is added to each input / output variable in the example set and the enlarged sample data set created thereby is used as the training set for constructing the artificial neural network model, the amount of noise to be added is specific to an input / output variable and its optimal value is determined using a stochastic search and optimization technique, namely, genetic algorithms, the network trained on the noise-superimposed enlarged training set shows significant improvements in its prediction accuracy and generalization performance, the invented methodology is illustrated by its successful application to the example data comprising instrumental errors and / or measurement noise from an industrial polymerization reactor and a continuous stirred tank reactor (CSTR).

Solid waste resource recovery in space is effected by pyrolysis processing, to produce light gases as the main products (CH4, H2, CO2, CO, H2O, NH3) and a reactive carbon-rich char as the main byproduct. Significant amounts of liquid products are formed under less severe pyrolysis conditions, and are cracked almost completely to gases as the temperature is raised. A primary pyrolysis model for the composite mixture is based on an existing model for whole biomass materials, and an artificial neural network models the changes in gas composition with the severity of pyrolysis conditions.