Abstract: A system and method to improve efficiency in aircraft maneuvers meant to accommodate time-related constraints in air traffic. Information related to flight performance and atmospheric conditions is gathered onboard an aircraft, then transmitted to an air traffic control center. In the event of a delay or any other event which necessitates an alteration in an aircraft trajectory, the data is sent to a decision support tool to compute and provide alternative trajectories, preferably including operator-preferred trajectories, within air traffic constraints. Air traffic controllers can then offer an alternative trajectory to an aircraft that is more efficient, cost effective, and/or preferable to the aircraft operator.

Abstract: Methods and system are provided for scheduling and negotiating air traffic within an airspace surrounding an airport and scheduled to land at the airport. An air traffic control (ATC) system is used to monitor the altitudes, speeds and lateral routes of aircraft. The ATC system generates a scheduled time-of-arrival (STA) at one or more meter fix points associated with the airport, the STA is stored, and data is received or inferred with the ATC system for at least a first of the aircraft, including a minimum fuel-cost speed and predicted trajectory parameters of the first aircraft based on current values of its existing trajectory parameters. Auxiliary data, including earliest and latest estimated time-of-arrival (ETAmin) and (ETAmax) at the meter fix point, STA being within/ outside ETAmin, ETAmax are generated, instructions are transmitted to the first aircraft, and the STA is updated for each aircraft stored in a queue.

Abstract: Methods and systems suitable for negotiating air traffic trajectory modification requests received from multiple aircraft that each has trajectory parameters. The methods include transmitting from at least a first aircraft a first trajectory modification request to alter the altitude, speed and/or lateral route thereof. A first conflict assessment is then performed to determine if the first trajectory modification request poses a conflict with the altitudes, speeds and lateral routes of other aircraft. If a conflict is not identified, the first trajectory modification request is granted and the first aircraft is notified of the first trajectory modification request being granted. Alternatively, if a conflict is identified, the first trajectory modification request is not granted and the first aircraft is notified thereof.

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: Methods and systems suitable for processing multiple trajectory modification requests received from multiple aircraft within an airspace.

Abstract: Methods and systems scheduling and negotiating air traffic within an airspace surrounding an airport and scheduled to land at the airport. An air traffic control (ATC) system is used to monitor the altitudes, speeds and lateral routes of aircraft as they enter the airspace. The ATC system generates a scheduled time-of-arrival (STA) for each aircraft at one or more meter fix points associated with the airport, the STA for each aircraft is stored, and data is received or inferred with the ATC system for at least a first of the aircraft, including a minimum fuel-cost speed and predicted trajectory parameters of the first aircraft based on current values of its existing trajectory parameters. Auxiliary data, including earliest and latest estimated time-of-arrival ETAmin and ETAmax at the meter fix point, are generated for the first aircraft using the predicted trajectory parameters. The ATC system determines whether the STA of the first aircraft is in or outside an ETA range bounded by its ETAmin and ETAmax.

Abstract: Methods and systems suitable for negotiating air traffic trajectory modification requests received from multiple aircraft that each has trajectory parameters. The methods include transmitting from at least a first aircraft a first trajectory modification request to alter the altitude, speed and/or lateral route thereof. A first conflict assessment is then performed to determine if the first trajectory modification request poses a conflict with the altitudes, speeds and lateral routes of other aircraft. If a conflict is not identified, the first trajectory modification request is granted and the first aircraft is notified of the first trajectory modification request being granted. Alternatively, if a conflict is identified, the first trajectory modification request is not granted and the first aircraft is notified thereof.

Abstract: A method for generating an optimized transition probability matrix (OTPM) is provided. The method is performed using a computer system coupled to a database. The method includes storing in the database financial data including obligor credit ratings, generating multi-period empirical transition probability matrices (ETPMs) for a selected time horizon using the financial data stored within the database, generating a mathematical expression to minimize a difference between target ETPM values and candidate OTPM values, and calculating the OTPM from the generated mathematical expression and the financial data stored within the database, wherein the calculated OTPM includes a first set of optimized transition probability values for predicting a likelihood that a credit rating of an obligor will migrate from one credit state to another credit state during a first time interval in the future.

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; committing the initial population of solutions to an initial population archive; performing a multi-objective process, based on the initial population archive and on multiple competing objectives, to generate an efficient frontier, the multi-objective process including a evolutionary algorithm process, the evolutionary algorithm process utilizing a dominance filter, the efficient frontier being used in investment decisioning.

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: Hybrid-heuristic optimization of competing portfolios of flight paths for flights through one or more sectors of an airspace represented by an air traffic system. In one embodiment, a hybrid-heuristic optimization process (100) includes one or more heuristic based processes (110), a genetic optimization process (120), an evaluation process involving an approximation model (130), an optimal portfolio selection process (140) and a validation process involving simulation (150) of the air traffic system.

Abstract: The present disclosure relates to the use of hybrid predictive models to predict one or more of performance, availability, or degradation of a power plant or a component of the power plant. The hybrid predictive model comprises at least two model components, one based on a physics-based modeling approach and one based on an observational or data-based modeling approach. The hybrid predictive model may self-tune or self-correct as operational performance varies over time.

Abstract: A method for advanced condition monitoring of an asset system includes monitoring a variable of an asset system using the at least one sensor of a smart sensor system; determining whether the asset system has departed from normal operation; and identifying the variable of the asset system indicating the departure from normal operation. In another method, the time sequential values of the monitored variable is analyzed by using a Rank Permutation Transformation test, a Hotelling's T2 statistic test, and a Likelihood Ratio Test; and a change of an operating condition of the asset system is determined using the analyzed values. An alert is provided if necessary. A smart sensor system includes an on-board processing unit for performing the method of the invention.

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, the generating the initial population of solutions of portfolio allocations including systematically generating the initial population of solutions to substantially cover the space defined by the competing objectives and the plurality of constraints; and generating an efficient frontier in the space based on the initial population, the efficient frontier for use in investment decisioning.

Abstract: A visual interactive multi-criteria decision-making method and computer-based apparatus for portfolio management. The method/apparatus supports partitioning of a portfolio of physical or other assets into two mutually exclusive categories, such as assets recommended for sale and assets recommended for retention. The method/apparatus utilizes one or more coupled 2-D projections of the portfolio in criteria space. The user interacts with the projections to express and record preferences.

Abstract: A method for multi-objective fault accommodation using predictive modeling is disclosed. The method includes using a simulated machine that simulates a faulted actual machine, and using a simulated controller that simulates an actual controller. A multi-objective optimization process is performed, based on specified control settings for the simulated controller and specified operational scenarios for the simulated machine controlled by the simulated controller, to generate a Pareto frontier-based solution space relating performance of the simulated machine to settings of the simulated controller, including adjustment to the operational scenarios to represent a fault condition of the simulated machine.

Abstract: A robust process for automating the tuning and maintenance of decision-making systems is described. A configurable multi-stage mutation-based evolutionary algorithm optimally tunes the decision thresholds and internal parameters of fuzzy rule-based and case-based systems that decide the risk categories of insurance applications. The tunable parameters have a critical impact on the coverage and accuracy of decision-making, and a reliable method to optimally tune these parameters is critical to the quality of decision-making and maintainability of these systems.

Abstract: A robust system for automating the tuning and maintenance of decision-making systems is described. A configurable multi-stage mutation-based evolutionary algorithm optimally tunes the decision thresholds and internal parameters of fuzzy rule-based and case-based systems that decide the risk categories of insurance applications. The tunable parameters have a critical impact on the coverage and accuracy of decision-making, and a reliable method to optimally tune these parameters is critical to the quality of decision-making and maintainability of these systems.

Abstract: A process 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 and system for automating the decision-making process used in underwriting of insurance applications is described. While this approach is demonstrated for insurance underwriting, it is broadly applicable to diverse decision-making applications in business, commercial, and manufacturing processes. A structured methodology is used based on a multi-model parallel network of multivariate adaptive regression splines (“MARS”) models to identify the relevant set of variables and their parameters, and build a framework capable of providing automated decisions. The parameters of the MARS-based decision system are estimated from a database consisting of a set of applications with reference decisions against each. Cross-validation and development/hold-out combined with re-sampling techniques are used to build a robust set of models that minimize the error between the automated system's decision and the expert human underwriter.