Abstract: A computer-implemented method is provided for model optimization. The method may include obtaining respective distribution descriptions of a plurality of input parameters to a model and specifying respective search ranges for the plurality of input parameters. The method may also include simulating the model to determine a desired set of input parameters based on a zeta statistic of the model and determining respective desired distributions of the input parameters based on the desired set of input parameters.

Abstract: A method is provided for a control system. The method may include obtaining data records associated one or more input variables and one or more output parameters, and selecting one or more input parameters from the one or more input variables. The method may also include generating a computational model indicative of interrelationships between the one or more input parameters and the one or more output parameters based on the data records, and determining desired respective statistical distributions of the one or more input parameters of the computational model.

Abstract: A method for diagnosing a system is provided. The method may include obtaining a plurality of input parameters from the system. The system may generate actual values of one or more output parameters based on the plurality of input parameters. The method may also include independently deriving values of the one or more output parameters, based on the plurality of input parameters, using a computational model, and detecting a divergence between the derived values and the actual values. Further, the method may include identifying respective desired statistic distributions of the plurality of input parameters, based on the actual values of the one or more output parameters, using the computational model.

Abstract: A computer-implemented method is provided for monitoring model performance. The method may include obtaining configuration information and obtaining operational information about a computational model and a system being modeled. The computational model and the system may include a plurality of input parameters and one or more output parameters. The system may generate respective actual values of the one or more output parameters, and the computational model may predict respective values of the one or more output parameters. The method may also include applying an evaluation rule from a rule set, based on the configuration information, to the operational information to determine whether the rule is satisfied.

Abstract: A computer-implemented method to provide a desired variable subset. The method may include obtaining a set of data records corresponding a plurality of variables and defining the data records as normal data or abnormal data based on predetermined criteria. The method may also include initializing a genetic algorithm with a subset of variables from the plurality of variables and calculating Mahalanobis distances of the normal data and the abnormal data based on the subset of variables. Further, the method may include identifying a desired subset of the plurality of variables by performing the genetic algorithm based on the Mahalanobis distances.

Abstract: A computer system for probabilistic modeling includes a display and one or more input devices. A processor may be configured to execute instructions for generating at least one view representative of a probabilistic model and providing the at least one view to the display. The instructions may also include receiving data through the one or more input devices, running a simulation of the probabilistic model based on the data, and generating a model output including a predicted probability distribution associated with each of one or more output parameters of the probabilistic model. The model output may be provided to the display.

Abstract: A method for designing a product includes obtaining data records relating to one or more input variables and one or more output parameters associated with the product. One or more input parameters may be selected from the one or more input variables, and a computational model indicative of interrelationships between the one or more input parameters and the one or more output parameters based on the data records may be generated. The method further includes providing a set of constraints to the computational model representative of a compliance state for the product and using the computational model to generate statistical distributions for the one or more input parameters and the one or more output parameters, based on the set of constraints, that represent a design for the product.

Abstract: The present invention includes a system and method configured to analyze a performance of a product. The product has associated process and performance characteristics. The method includes the steps of establishing a plurality of process characteristics associated with the product, establishing an analysis relationship between the process characteristics and the performance characteristic, and analyzing the performance characteristic of the product in response to the relationship.