Abstract: A method to predict remaining life of a target is disclosed. The method includes receiving information regarding a behavior of the target, and identifying from a database at least one piece of equipment having similarities to the target. The method further includes retrieving from the database data prior to an end of the equipment useful life, the data having a relationship to the behavior, evaluating a similarity of the relationship, predicting the remaining life of the target based upon the similarity, and generating a signal corresponding to the predicted remaining equipment life.

Abstract: A system and method for monitoring the vibrations of a machine that includes a reflective patch affixed to the machine and a vibration detection unit including an optics module. The optics module may be positioned remotely from the machine such that the optics module transmits an electromagnetic beam to the reflective patch and reflected from the reflective patch to the optics module. The optics module demodulates the electromagnetic beam to determine the vibration of the machine.

Abstract: The systems and methods of the invention are directed to portfolio optimization and related techniques. For example, the invention provides a method for multi-objective portfolio optimization for use in investment decisions based on competing objectives and a plurality of constraints constituting a portfolio problem, the method sequentially comprising: generating a non-dominated solution set in a space; applying a first set of user-specified constraints to reduce the solutions in the non-dominated solution set to a solution subset; and executing a series of local tradeoffs on the solution subset to result in a resulting solution subset, the local tradeoffs being performed in a lower dimension performance space as compared to the space, and the solution subset being used in investment decisioning.

Abstract: A system for at least a partial underwriting of insurance policies is described. based on the similarity to previous insurance applications, a decision on the current request for underwriting may be made. this decision-making process represents an analogical approach to the placement of an insurance application to an underwriting category, whereby a given insurance application request is compared to previous requests.

Abstract: A method for advanced condition monitoring of an asset system includes sensing actual values of an operating condition for an operating regime of the asset system using at least one sensor; estimating sensed values of the operating condition by using an auto-associative neural network; determining a residual vector between the estimated sensed values and the actual values; and performing a fault diagnostic on the residual vector. In another method, an operating space of the asset system is segmented into operating regimes; the auto-associative neural network determines estimates of actual measured values; a residual vector is determined from the auto-associative neural network; a fault diagnostic is performed on the residual vector; and a change of the operation of the asset system is determined by analysis of the residual vector. An alert is provided if necessary. A smart sensor system includes an on-board processing unit for performing the method of the invention.

Abstract: A method for advanced condition monitoring of an asset system includes sensing actual values of an operating condition for an operating regime of the asset system using at least one sensor; estimating sensed values of the operating condition by using an auto-associative neural network; determining a residual vector between the estimated sensed values and the actual values; and performing a fault diagnostic on the residual vector. In another method, an operating space of the asset system is segmented into operating regimes; the auto-associative neural network determines estimates of actual measured values; a residual vector is determined from the auto-associative neural network; a fault diagnostic is performed on the residual vector; and a change of the operation of the asset system is determined by analysis of the residual vector. An alert is provided if necessary. A smart sensor system includes an on-board processing unit for performing the method of the invention.

Abstract: A method for advanced condition monitoring of an asset system includes using a plurality of auto-associative neural networks to determine estimates of actual values sensed by at least one sensor in at least one of the plurality of operating regimes; determining a residual between the estimated sensed values and the actual values sensed by the at least one sensor from each of the plurality of auto-associative neural networks; and combining the residuals by using a fuzzy supervisory model blender; performing a fault diagnostic on the combined residuals; and determining a change of the operation of the asset system by analysis of the combined residuals. An alert is provided if necessary. A smart sensor system includes an on-board processing unit for performing the method of the invention.

Abstract: A risk classification technique that exploits the existing risk structure of the decision problem in order to produce risk categorizations for new candidates is described. The technique makes use of a set of candidates for which risk categories have already been assigned (in the case of insurance underwriting, for example, this would pertain to the premium class assigned to an application). Using this set of labeled candidates, the technique produces two subsets for each risk category: the Pareto-best subset and the Pareto-worst subset by using Dominance. These two subsets can be seen as representing the least risky and the most risky candidates within a given risk category. If there are a sufficient number of candidates in these two subsets, then the candidates in these two subsets can be seen as samples from the two hypothetical risk surfaces in the feature space that bound the risk category from above and below respectively.

Abstract: A risk classification technique that exploits the existing risk structure of the decision problem in order to produce risk categorizations for new candidates is described. The technique makes use of a set of candidates for which risk categories have already been assigned (in the case of insurance underwriting, for example, this would pertain to the premium class assigned to an application). Using this set of labeled candidates, the technique produces two subsets for each risk category: the Pareto-best subset and the Pareto-worst subset by using Dominance. These two subsets can be seen as representing the least risky and the most risky candidates within a given risk category. If there are a sufficient number of candidates in these two subsets, then the candidates in these two subsets can be seen as samples from the two hypothetical risk surfaces in the feature space that bound the risk category from above and below respectively.

Abstract: A method to reduce uncertainty bounds of predicting a remaining life of a probe using a set of diverse models is disclosed. The method includes generating an estimated remaining life output by each model of the set of diverse models, aggregating each of the respective estimated remaining life outputs via a fusion model, and in response to the aggregating, predicting the remaining life, the predicting having reduced uncertainty bounds based on the aggregating. The method further includes generating a signal corresponding to the predicted remaining life of the probe.

Abstract: The systems and methods of the invention are directed to portfolio optimization and related techniques. For example, the invention provides a method for multi-objective portfolio optimization for use in investment decisions based on competing objectives and a plurality of constraints constituting a portfolio problem, the method comprising: generating an initial population of solutions of portfolio allocations; performing a first multi-objective process, based on the initial population and the competing objectives, to generate a first interim efficient frontier; performing a second multi-objective process, based on the initial population and the competing objectives, to generate a second interim efficient frontier; and fusing the first interim efficient frontier with the second interim efficient frontier to create an augmented efficient frontier for use in investment decisioning.

Abstract: A method and system for automatically developing a fault classification system from time series data. The sensors need not have been intended for diagnostic purposes (e.g., control sensors). These methods and systems are functionally independent of knowledge related to a particular equipment system, thereby allowing seamless application to multiple systems, regardless of the suite of sensors in each system. Because this algorithm is totally automated, substantial savings in time and development cost can be achieved. The algorithm results in a classification system and a set of features that might be used to develop alternative classification systems without human intervention.

Abstract: A method and system of forecasting reliability of an asset is provided. The method includes identifying peer units of the asset by using selected criteria, performing a search for the peer units based upon the selected criteria, and constructing local predictive models using the peer units. The method also includes estimating the future behavior of the asset based upon the local predictive models and dynamically updating the local predictive models to reflect at least one change in the criteria.

Abstract: A method and system for fusing a collection of classifiers used for an automated insurance underwriting system and/or its quality assurance is described. Specifically, the outputs of a collection of classifiers are fused. The fusion of the data will typically result in some amount of consensus and some amount of conflict among the classifiers. The consensus will be measured and used to estimate a degree of confidence in the fused decisions. Based on the decision and degree of confidence of the fusion and the decision and degree of confidence of the production decision engine, a comparison module may then be used to identify cases for audit, cases for augmenting the training/test sets for re-tuning production decision engine, cases for review, or may simply trigger a record of its occurrence for tracking purposes. The fusion can compensate for the potential correlation among the classifiers.

Abstract: The systems and methods of the invention are directed to portfolio optimization and related techniques. For example, the invention provides a method for multi-objective portfolio optimization for use in investment decisions based on competing objectives and a plurality of constraints constituting a portfolio problem, the method comprising: performing a first multi-objective optimization process, based on competing objectives, to generate an efficient frontier of possible solutions; observing the generated efficient frontier; based on the observing, identifying an area of the efficient frontier in which there is a gap; and effecting a gap filling process by which the efficient frontier is supplemented in the area of the gap, the efficient frontier being used in investment decisioning.

Abstract: A system and method for processing healthcare service data is herein disclosed. The system comprising a decision engine in communication with a process manager and a knowledge source. The decision engine receives at least one protocol from the knowledge source that is derived by automated learning and applies the at least one protocol to healthcare service data and transmits a response to the process manager such that the response is indicative of a next workflow step to be taken.

Abstract: A method to reduce uncertainty bounds of predicting a remaining life of a probe using a set of diverse models is disclosed. The method includes generating an estimated remaining life output by each model of the set of diverse models, aggregating each of the respective estimated remaining life outputs via a fusion model, and in response to the aggregating, predicting the remaining life, the predicting having reduced uncertainty bounds based on the aggregating. The method further includes generating a signal corresponding to the predicted remaining life of the probe.

Abstract: A method to predict equipment life is disclosed. The method includes making available a set of input parameters, and defining a model of a health of the equipment as a function of the set of input parameters. The method continues with receiving at least one signal representative of a respective one of an actual sensor output relating to an actual operation attribute margin of the equipment, predicting a remaining useful equipment life based upon a sequence of outputs of the model of the health of the equipment, and generating a signal corresponding to the remaining useful equipment life.

Abstract: Systems and methods for multi-level optimization of emission levels and efficiency for a boiler system that includes creating both boiler-level models and burner-level models and receiving a plurality of boiler-level system variables. The received system variables are used along with boiler system constraints to optimize boiler-level setpoints. Once the boiler-level setpoints have been optimized they are sent to the burner level of a hierarchical control system, where they are used to optimize burner-level setpoints. Once the burner-level setpoints have been optimized they are sent to the burner control loops of the plant control system to be implemented.

Abstract: A method to predict remaining life of a target is disclosed. The method includes receiving information regarding a behavior of the target, and identifying from a database at least one piece of equipment having similarities to the target. The method further includes retrieving from the database data prior to an end of the equipment useful life, the data having a relationship to the behavior, evaluating a similarity of the relationship, predicting the remaining life of the target based upon the similarity, and generating a signal corresponding to the predicted remaining equipment life.