摘要:
A method for extracting as knowledge causal relationships between input variables and an output variable of a neural circuit model, said neural circuit model being of a hierarchical structure constructed of an input layer, at least one hidden layer and an output layer and having performed learning a limited number of times by determining weight factors between mutually-connected neuron element models in different layers of the input layer, hidden layer and output layer, wherein with respect to plural routes extending from a neuron element model, corresponding to a particular input variable, of the input layer to a neuron element model, corresponding to a particular output variable, of the output layer by way of the individual neuron element models of the hidden layer, a product of the weight factors for each of the routes is determined, and the products for the plural routes are summed, whereby the sum is employed as a measure for the determination of the causal relationship between the particular input variable and the particular output variable.
摘要:
A thermal transfer recording sheet comprising a substrate and ink layer formed thereon containing one or more sublimable dyes and a high-molecular-weight polyamide obtained from dimer acids as a binder is good in adherence of the ink layer to the substrate, and thermal transfer properties to give clear color hard copies.
摘要:
A thermal transfer recording sheet comprising a substrate and ink layer formed thereon containing one or more sublimable dyes and a high-molecular-weight polyamide obtained from dimer acids as a binder is good in adherence of the ink layer to the substrate, and thermal transfer properties to give clear color hard copies.
摘要:
This invention discloses a method and a system of making a neuron network model learn the typical past process control results and utilizing this model for the supporting of an operation of a process. The neuron network is given a typical pattern of a plurality of input variables at different points in time as input signals, and is taught corresponding control variables as teaching signals, and untaught input patterns are given to this intelligent neuron network model to have it determine corresponding control variables. A plurality of patterns at predetermined time intervals are preferably used at once as patterns to be taught.
摘要:
A method for extracting as knowledge causal relationships between input variables and an output variable of a neural circuit model, said neural circuit model being of a hierarchical structure constructed of an input layer, at least one hidden layer and an output layer and having performed learning a limited number of times by determining weight factors between mutually-connected neuron element models in different layers of the input layer, hidden layer and output layer, wherein with respect to plural routes extending from a neuron element model, corresponding to a particular input variable, of the input layer to a neuron element model, corresponding to a particular output variable, of the output layer by way of the individual neuron element models of the hidden layer, a product of the weight factors for each of the routes is determined, and the products for the plural routes are summed, whereby the sum is employed as a measure for the determination of the causal relationship between the particular input variable and the particular output variable.