Abstract: A method for predicting or detecting an event in turbomachinery includes the steps of obtaining operational data from at least one machine and at least one peer machine. The operational data comprises a plurality of performance metrics. A genetic algorithm (GA) analyzes the operational data, and generates a plurality of clauses, which are used to characterize the operational data. The clauses are evaluated as being either “true” or “false”. A fitness function identifies a fitness value for each of the clauses. A perturbation is applied to selected clauses to create additional clauses, which are then added to the clauses group. The steps of applying a fitness function, selecting a plurality of clauses, and applying a perturbation can be repeated until a predetermined fitness value is reached. The selected clauses are then applied to the operational data from the machine to detect or predict a past, present or future event.

Abstract: A method for predicting or detecting an event in turbomachinery includes the steps of obtaining operational data from at least one machine and at least one peer machine. The operational data comprises a plurality of performance metrics. A genetic algorithm (GA) analyzes the operational data, and generates a plurality of clauses, which are used to characterize the operational data. The clauses are evaluated as being either “true” or “false”. A fitness function identifies a fitness value for each of the clauses. A perturbation is applied to selected clauses to create additional clauses, which are then added to the clauses group. The steps of applying a fitness function, selecting a plurality of clauses, and applying a perturbation can be repeated until a predetermined fitness value is reached. The selected clauses are then applied to the operational data from the machine to detect or predict a past, present or future event.

Abstract: A set of pluggable rules are used to define low-level security rules in terms of high-level security concepts. The rules are part of a pluggable module that can interact with a business logic to provide different granularities of control.

Abstract: A method is provided for visualizing a probabilistic output result generated by a business information and decisioning control system for a business including multiple interrelated business processes. The method includes: (a) performing analysis using a business model provided by the business information and decisioning control system to generate a probabilistic output result, the probabilistic output result having confidence information associated therewith; (b) presenting the probabilistic output result and the associated confidence information to the user via a business system user interface of the business information and decisioning control system; and (c) receiving the user's selection of a command via the business system user interface, where the command prompts at least one of the interrelated business processes to make a change in the at least one of the interrelated business processes.

Abstract: A set of pluggable rules are used to define low-level security rules in terms of high-level security concepts. The rules are part of a pluggable module that can interact with a business logic to provide different granularities of control.

Abstract: A software architecture permits efficient construction of server software applications for many diverse domains. The architecture implements and enforces constraints that customize the behavior of the application. The constraints can be imposed by a variety of sources (e.g., legal, operating company, customers, end users, cultural customs, etc.). A constraint resolver resolves the constraints at run time, or prior to run time, so that the application behaves and appears appropriately for the given set of constraints.